ProfitMaximizationforWasteFurnitureRecycledinTaiwan...

Research ArticleProfit Maximization for Waste Furniture Recycled in TaiwanUsing Cradle-to-Cradle Production Programming

Chun-Wei Remen Lin12 Min-Tsung Chen2 Ming-Lang Tseng 134 Anthony S F Chiu5

and Mohd Helmi Ali67

1Institute of Innovation amp Circular Economy Asia University Taichung City Taiwan2Department of Business Administration Asia University Taichung City Taiwan3Department of Medical Research China Medical University Hospital China Medical University Taichung City Taiwan4Faculty of Economic and Management University Kebangsaan Malaysia Bangi Malaysia5Department of Industrial Engineering De La Salle University Manila Philippines6Centre of Global Business amp Digital Economy Faculty of Economics and Management Universiti Kebangsaan MalaysiaBangi 43000 Selangor Malaysia7University of Cambridge Cambridge UK

Correspondence should be addressed to Ming-Lang Tseng tsengminglanggmailcom

Received 19 April 2020 Accepted 11 May 2020 Published 16 July 2020

Guest Editor Kuei-Hu Chang

Copyright copy 2020 Chun-Wei Remen Lin et al)is is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work isproperly cited

)is study proposes the use of cradle-to-cradle production programming for waste furniture and aims to achieve optimal ef-ficiency by reusing waste furniture and maximizing the corresponding benefits so that the furniture industry is in line with cradle-to-cradle manufacturing )is study is increasingly important to manage products through a comprehensive green reverselogistics system that consists of three procedures ie recycling reuse and remanufacturing of waste items )is study proposes amathematical formula to establish a cradle-to-cradle production programming model for waste furniture )e fuzzy set theory isused to define the attributes that reflect production and market demands such as degree of damage technical feasibility marketdemands environmental protection laws and regulations and environmental performance In addition particle swarm opti-mization is adopted to ascertain the optimal profit from waste furniture sales )rough situational simulations and analyses thefuzzy set information from Taiwan Germany and China is compared)e result reveals that the qualitative information proposedhas a significant impact on the profit of waste furniture reuse )e production model can effectively assist in the productionprogramming of waste furniture thereby optimizing profit for cradle-to-cradle production planning

1 Introduction

Taiwan introduced the Resource Recycling Act which aimsto establish proper disposal of waste products to advocatecomplete recycling and reuse of resources to save naturalresources to reduce environmental loads and to establish asustainable society Subsequently the Taiwan Environ-mental Protection Administration [1 2] initiated the BulkyWaste Recycling and Reuse program and assisted countiesand cities in its implementation in 2003 In March 2004 theTEPA initiated a garbage classification program the goal

being zero waste disposal )e cleanup operation for generalhousehold waste was driven by zero waste and waste re-duction guidelines in source and resource recycling )egovernment continued the implementation of the BulkyWaste Recycling and Reuse program with its incorporationinto the 2007ndash2012 Recycling Program for General WasteResources)e cradle-to-cradle (C2C) concept for industrialproducts was globally acknowledged as a replacement for thecradle-to-grave concept due to the increasing awareness ofthe need for environmental protection [3ndash5] )e C2Cconcept meant that the waste from certain products would

HindawiMathematical Problems in EngineeringVolume 2020 Article ID 2948049 15 pageshttpsdoiorg10115520202948049

serve as the raw material of newly produced items and thatstep in the manufacturing process would comply with en-vironmental protection laws and regulations to reduce re-source consumption and harmful emissions In this waysustainability could be achieved [6ndash8] Moreover customerswould now pay closer attention to whether products thatwere at the end of their useful life were to be disposed ofrecycled or reused due to environmental protectionawareness It has been discarded ldquowastesrdquo can be recycledreduced and reused (3Rs) and be more valuable [9ndash11]

In the literature Fujii et al [9] discussed the demand forrecycled products economic conditions weight reductionproduct reuse and quantity and types of competitiverecycled products they developed a social system for cus-tomer purchases that influence waste generation Pandeyet al [12] promoted reuse and recycling practices in reducingwastes and analyzed the practices that help in reducing thegeneration of waste Tseng et al [11] indicated that there wasinterdependence and interrelationships among the attri-butes along with a lack of operational data-driven andoptimization solutions in supply chain networks to optimizeefficiency Tam et al [13] proposed waste materials needed tobe efficiently returned for production and the time-testedprocesses of reuse recovery and recycling (3Rs) were es-sential )e attributes were usually developed from quali-tative information and quantitative data were used indecision-making However prior studies did not explainhow the attributes worked together to enhance the demandfor recycled products and such studies ignored the way theattributes were qualitative in measure and used onlyquantitative data [4 14 15] In addition there was a need toanalyze the 3Rs in the optimization solution

However bulky waste is difficult to collect and removeregularly )ere is no complete recycling system and theresources are not used effectively With the promotion ofrelevant recycling programs bulky waste such as wastefurniture that still has value is repaired and reused In thisway the bulky waste as well as the environmental loads canbe effectively reduced an effect which is conducive to thegoal of zero waste disposal )e fuzzy set theory deals withqualitative information It is arguable that bulky waste is away to generate profit in the value chain [8 16 17] Hencefor this study production programming is expected forwaste furniture so that the maximum reuse rate can beachieved)erefore this study aims to establish the model ofreusing the waste furniture to obtain the maximum profitfrom waste product sales )is study has established the C2Crecycling production planning model for waste furniturethrough a mathematical model It is hoped that with thismodel waste furniture is effectively recycled and reusedrecycling profit can be maximized and optimal remanu-facturing volume is obtained [18] In addition this study hasprovided situational simulations to verify the optimality ofthe model

)is study focuses on waste furniture recycling andremanufacturing the furniture through recycling centersunder the TEPA jurisdiction includes the cleaning teamsthat are responsible for removing and transporting wastefurniture as well as the processing centers in which waste

furniture is processed for reuse and remanufacturing In theprocessing centers reusable waste furniture is repairedreusable parts are disassembled and the parts beyond repairare crushed )is study takes into account the followingcosts recycling cost repair cost disassembly cost andcrushing cost )e study does not consider the inventorycost For the purchase cost only the cost of new raw ma-terials is taken into consideration

)e rest of this study is organized as follows Section 2 isthe theoretical background method and industrial back-ground are described in Section 3 Section 4 presents theresults and the sensitivity analysis lastly the concludingremarks are discussed

2 Literature Review

Sustainable development was first proposed by the WorldCommission on Environment and Development of theUnited Nations (1987) )is proposal aimed to meet theneeds of the present without compromising the ability offuture generations to meet their own needs [19 20] Inaddition Braat [21] proposed that sustainable develop-ment should include three principles ie fairness sus-tainability and commonality and economic developmentshould be pursued based on the sustainable developmentof the ecological environment and promoted around theworld [10 22 23] Wong et al [24] used sustainable de-velopment assessment to achieve social environmentaland economic benefits and created an assessment modelusing qualitative information and quantitative dataHowever sustainable development included recyclingend-of-life products while the planning and performanceevaluation of recycling end-of-life product plans ensuredthat collected recyclable materials as well as the assess-ment of environmental impacts did not increase thoseimpacts Xu et al [25] explored sustainable developmentdriving forces to assess sustainability in China In additionthe assessment of social environmental and economicbenefits was performed using qualitative and quantitativemeasures Prior studies were usually lacking in attributesanalysis

Lin et al [3] highlighted the clean cycle strategy andpresented better recycled product qualities and less dissi-pation of hazardous substances during recycled productusage )is study ignored CO2 emissions during therecycled production process Being free of hazardoussubstances was always required in the new productionmanufacturing process Nurjanni et al [26] presented amultiobjective optimization mathematical model to reducecosts and minimize environmental pollution through atrade-off between financial and environmental issuesHowever the business model is needed to balance thesocial economic and environmental impacts Sultan et al[27] presented the mixture of materials and the separationof materials that make up a product as a model of thedesirability of recycling end-of-life products Lin et al [4]developed a cradle-to-cradle fuzzy recycling productionplanning model for a green product using the failure modeand effects analysis technique along with the Taguchi

2 Mathematical Problems in Engineering

experimental design method However the performanceevaluation system had to involve the qualitative informa-tion and quantitative data to create the optimal recycledproduction plan and estimate the attributes related to the3Rs

3 Method

)is section includes the 3Rs on waste furniture and theproposed method

31 3Rs onWaste Furniture )e data updated by the TEPAin 2012 about the condition of recycling bulky waste andwaste furniture collated the current situation as follows (1)the method of cleaning up waste furniture includes havingthose who generate the waste (most of them) notifying theexecutive authorities (cleaning teams) to remove it andpays the private sectors to remove it After the wastefurniture is recycled most of it is manually sorted and asmall part of it is sorted by machine)e damaged furnitureis often resold to the public for reuse after it has beenrepaired by professionals (2) Most waste furniture can bereused However due to its large size collecting and re-moving the furniture at regular intervals is difficult Inaddition a complete recycling system is rarely seen inTaiwan

)erefore the waste furniture is mostly incinerated orburied )e resources are not used effectively and even theenvironment has been affected by the means of waste dis-posal [28 29] (3) Waste furniture can reenter the market asproducts after being properly repaired while recycled re-sources from waste furniture can reenter the market as rawmaterials which reduces the environmental loads by low-ering the amount of waste for incineration or landfill dis-posal )e category as well as the worn-out condition of theabandoned furniture determines the best way to reuse itincluding repair disassembly and crushing )e first step toreduce waste is to extend the useful life of the furniture byrepairing the damaged item and reusing it Different types offurniture can be repaired after cost performance is con-sidered from the perspectives of the degree of damage andthe ease of repair

32 Proposed Approach )is study uses particle swarmoptimization (PSO) to find solutions )e advantages ofusing PSO are that only a few parameters need to be adjustedand that it can be used to solve most optimization problems)e PSO is a heuristic algorithm of swarm intelligence andobserves how a flock of birds flies and hunts for food Itsimulates the flock of birdrsquos method of communication tofind the optimal solution [30ndash32] Furthermore a mecha-nism of evolutionary computation is established accordingto the best flight of a single bird and that of a flock of birdsDimension d (1le dleD) of a particle updates its own speedand position with the following equation when the particlebest (pbest) and the global best (gbest) are found for eachgeneration

vi d(t + 1) w middot vi d(t) + c1 middot r1 middot pi d minus xi d(t)1113858 1113859

+ c2 middot r2 middot pg d minus xi d(t)1113960 1113961

xi d (t + 1) xi d(t) + vi d(t + 1)

(1)

where ]i d (t + 1) is the new speed of particle i ]i d (t) is theoriginal speed of particle i w is the inertia weight c1 and c2are learning factors r1 and r2 random numbers between 0and 1 χi d (t + 1) is the new position of particle i χi d (t) is theoriginal position of particle i pi d is the individual bestposition of particle i (pbest) and pgd is the global bestposition (gbest)

33 C2CWaste FurnitureManufacturing Process )is studyformulates C2C programming for manufacturing recycledwaste furniture It mainly focuses on the remanufacturing ofwaste furniture and reproduction with the crushed wastefurniture as raw materials )is study aims to establish agreen production model that maximizes benefits with thegoal of achieving zero waste during the disposal of wastefurniture for reuse )e C2C process for waste furniture isshown in Figure 1 )is study discusses the waste furnitureC2C production process after waste furniture is producedand removed

34 5e Establishment of the Model Parameter descriptionsare as follows

(1) i the batch of waste furniture being recycled forremanufacturing i 1 N

(2) 1113957ai1113957d the fuzzy information for waste furniture pro-duction planning

(3) 1113957ui1113957vi the fuzzy information for crushing wastefurnitureDecision variables are as follows

(4) Xi the proportion of waste furniture Batch i madeinto remanufactured furniture

(5) Di the proportion of waste furniture Batch i dis-assembled into reusable raw materials

(6) Ui the proportion of waste furniture Batch i madeinto coarsely crushed materials

(7) V i the proportion of waste furniture Batch i madeinto finely crushed materials

)e schematic diagram shown in Figure 2 includes theremoval and reuse of waste wood furniture the reusableitems include remanufactured furniture coarsely crushedmaterials and finely crushed materials

35 Mathematical Model

351 Construct an Objective Function )e profit onrecycled waste furniture for reuse remanufactured furni-ture sales revenue + crushed material sales revenue-ndash(recycling waste furniture cost + the cost of disassemblingwaste furniture into reusable materials + repair cost for

Mathematical Problems in Engineering 3

The demand for furniture

Furniture remanufacturing Raw materials

Consumers

Waste furniture removal

Waste furniture weighing

Categorization

Disassemblingfurniture for reuse

Coarsely and finely

crushing

Remanufacturedfurniture

Composting Materials for remanufacturing Fueling

Plantingtrees Ashes

The reuse demand

Repair

Sorting

The materials disassembled

from old furniture for

reuse

A small partof damage

A large partof damage

Partial damage

Figure 1 )e C2C production programming for waste furniture

Cleaning team Processing center

WM2

WMi

Coarsely crushing

Finely crushing

Raw material supplier

WM1

DFMi

Disassemble

Repair

CMi

CrushCCMi

CFMi

RFi

RMPi

NMi

Vi

Remanufactured furniture

Ui

Xi

1

2

iũi vi

d ixi

Di

Physical logistics Reverse logistics Information flow

Figure 2 )e schematic diagram for the production programming model


remanufactured furniture + coarsely crushing cost of wastefurniture + finely crushing cost of waste furniture)

1113957Z 1113944N

i1PSGi + 1113944

N

i1RSUi

minus 1113944N

i1RCi + DP Ci + PCi + BCCi + BFCi( 1113857

(2)

Explanation of the Objective Function

(1) Remanufactured Furniture Sales Revenue )e remanu-factured furniture sales revenue the amount of remanu-factured furnituretimes the unit price of remanufacturedfurniture

1113944

N

i1PSGi 1113944

N

i1RFi times FPi( 1113857

RFi WMi times 1113957Xi( 1113857 + NMi

(3)

)e total amount of waste furniture that has beenrepaired the total amount of recycled waste furniture ofBatch i WMi times the proportion of recycled furniture madeinto remanufactured furniture 1113957Xi + the amount of newmaterials invested in remanufactured furniture [33ndash35] )eoperational rule of fuzzy numbers and the application ofmembership functions propose the use of the fuzzy theory tosolve uncertainty and ambiguity in the real world

1113957xi and 1113957di are the fuzzy information of waste furnitureproduction programming After calculating the fuzzy in-formation the proportion of recycled waste furniture madeinto remanufactured furniture 1113957Xi (a fuzzy value) and thereuse rate of disassembled waste furniture 1113957Di (a fuzzy value)can be obtained )e calculation of fuzzy information will befurther introduced in Section 34

(2) 5e Sales Revenue of Crushed Waste Furniture )e salesrevenue of crushed waste furniture coarsely crushedmaterials from waste furniture times the unit price of thecoarsely crushed materials + finely crushed materials fromwaste furniture times the unit price of the finely crushedmaterials

1113944N

i1RSUi 1113944

N

i1CCMi times CMPi + FCMi times FMPi( 1113857

CCMi CMi times 1113957Ui

FCMi CMi times 1113957Vi

(4)

)e total amount of coarsely crushed materials fromwaste furniture the total amount of recycled furniture ofthe ith batch WMi times the proportion of the waste furniturethat has been coarsely crushed 1113957Ui

)e total amount of finely crushed materials from wastefurniture the total amount of recycled furniture of the ithbatch WMi times the proportion of the waste furniture that hasbeen finely crushed 1113957Vi

1113957ui and 1113957vi are the fuzzy information of waste furnitureproduction programming After calculating the fuzzy in-formation the fuzzy values for 1113957Ui and 1113957Vi can be obtained)e calculation of fuzzy information will be further intro-duced in Section 34

(3) 5e Cost of Recycling Waste Furniture )e cost ofrecycling waste furniture the amount of waste furniturethat the cleaning team has removed and transportedtimes theunit price of recycling waste furniture

1113944N

i1RCi 1113944

N

i1WMi times CC( 1113857 (5)

(4) 5e Cost of Disassembling Waste Furniture into ReusableMaterials )e cost of disassembling waste furniture intoreusable materials the amount of waste furniture that hasbeen disassembled for reusetimes the unit price of the dis-assembled reusable materials

1113944N

i1DP Di 1113944

N

i1DF Mi times DC( 1113857

DF Mi WMi times 1113957Di

(6)

)e waste furniture that is beyond repair but can still bereused is disassembled into reusable materials )e amount ofreclaimed materials from disassembled waste furniture thetotal amount of recycled waste furniture of Batch iWMi

times theproportion of waste furniture disassembled for reuse 1113957Di

(5) 5e Cost of repairing Waste Furniture )e cost ofrepairing waste furniture the amount of remanufacturedfurnituretimes the unit price of the remanufactured furnitur-e + the newmaterials used for repairing waste furnituretimes theunit price of the new materials

1113944N

i1DP Ci 1113944

N

i1RFi times RC + NMi times NMC( 11138571113858 1113859 (7)

)e cost of repairing waste furniture primarily includeslabor and the newmaterials used for repairingRC representsthe labor cost NMi represents the new materials used forrepairing waste furniture and NMC represents the unitprice of the new materials

(6) 5e Cost of Coarsely Crushing Waste Furniture for Reuse)e cost of coarsely crushing waste furniture for reuse theamount of coarsely crushed materialstimes the unit price ofcoarsely crushing waste furniture


1113944

N

i1BCCi 1113944

N

i1CCMi times CCC( 1113857 (8)

(7) 5e Cost of Finely Crushing Waste Furniture for Reuse)e cost of finely crushing waste furniture for reuse theamount of finely crushed materialstimes the unit price of finelycrushing waste furniture

1113944N

i1BFCi 1113944

N

i1FCMi times FCC( 1113857 (9)

352 Constraint )e constraints are explained as follows

RFi + DF Mi + CCMi + FCMi( 1113857leTMi (10)

CCMi + FCMi leCMi (11)

1113957Xi + 1113957Di + 1113957Ui + 1113957Vi le 1 (12)

WMi times 1113957xi leR times RTi (13)

WMi times 1113957yi leDl times DTi (14)

WMi times 1113957ui leC times CTi (15)

WMi times 1113957vi leF times FTi (16)

TMiWMiRFi DF MiCMi CCMi FCMiNMi ge 0

(17)

0lexi le 1 0leyi le 1 0le ui le 1 0le vi le 1 (18)

(i) Constraint (10) the amount of remanufacturedfurniture reusable parts disassembled from wastefurniture and crushed waste furniture shall notexceed the total amount of recycled waste furnitureand new raw materials

(ii) Constraint (11) the total amount of the materialsfrom coarsely and finely crushed furniture is lessthan the total amount of crushed wastefurniture

(iii) Constraint (12) the total of the following theproportion of recycled waste furniture that hasbeen used in remanufacturing the proportion ofwaste furniture that has been disassembled forreuse and the proportion of waste furniture

crushed for reuse should not exceed the overallproportion of recycled waste furniture le 1

(iv) Constraint (13) the output of remanufacturedfurniture does not exceed the maximum repairablecapacity of the remanufacturing center

(v) Constraint (14) the amount of waste furnituredisassembled for reuse does not exceed the max-imum disassembling capacity of the remanu-facturing center

(vi) Constraint (15) the amount of coarsely crushedwaste furniture does not exceed the maximumcoarsely crushing capacity of the remanufacturingcenter

(vii) Constraint (16) the amount of finely crushedwaste furniture does not exceed the maximumfinely crushing capacity of the remanufacturingcenter

(viii) Constraint (17) the amount of each material mustbe greater than zero

(ix) Constraint (18) the value of decision variablesranges between 0 and 1

36 Establish a Mode for Computing Fuzzy Values

361 Establishment of Fuzzy Information 1113957xi and 1113957diFirst define the three inputs and establish the threemembership functions

(i) )e membership function for the productdamage degree is almost damaged quite worn-out average many reusable parts reusable inwhole )e trigonometric function for it isμ1113957x(a) [045 075]

(ii) )e membership function for technical repair fea-sibility is extremely low reparability low repar-ability average high reparability extremely highreparability )e trigonometric function for this isμ1113957x(t) [045 075]

(iii) )e membership function for product market de-mand is extremely low relatively low averagerelatively high extremely high )e trigonometricfunction for this is μ1113957x(m) [025 065]

1113957xi and 1113957di are the fuzzy production volume of remanu-factured furniture under waste furniture production pro-gramming and the fuzzy amount of reusable raw materialsdisassembled from waste furniture respectively )ey areboth affected by three fuzzy information factors the degreeof damage the repair feasibility and the market demand)eir fuzzy functions are as follows


1113957x f μ1113957x(a) μ1113957x(t) μ1113957x(m)( 1113857

0 if alt 045 or tlt 045 ormlt 025

(a minus 045)(t minus 045)(m minus 025)

0036 if 075gt age 045 and 075gt tge 045 and 065gtmge 025

(a minus 045)(t minus 045)

009 if 075gt age 045 and 075gt tge 045 andmge 065

(t minus 045)(m minus 025)

012 if age 075 and 075gt tge 045 and 065gtmge 025

(a minus 045)(m minus 025)

012 if 075gt age 045 and tge 075 and 065gtmge 025

t minus 04503

if age 075 and 075gt tge 045 andmge 065

a minus 04503

if 075gt age 045 and tge 075 andmge 065

m minus 02504

if age 075 and tge 075 and 065gtmge 025

1 if age 075 and tge 075 andmge 065

⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

1113957d f μ1113957d(a) μ1113957d

(t) μ1113957d(m)1113874 1113875










t minus 04503


a minus 04503


m minus 02504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(19)

Calculation of fuzzy information 1113957xi this study proposesfuzzy evaluation values for remanufactured furniture in

Taiwan 3 for the product damage degree (ordinary) 4 forrepair feasibility (high reparability) and 2 for product


market demand (relatively low))erefore the fuzzy value of1113957xi is inferred as 1113957x 0105

1113957x f μ1113957x(a) μ1113957x(t) μ1113957x(m)( 1113857 (06 minus 045)(066 minus 045)(037 minus 025)

0036 0105 (20)

Calculation of fuzzy information 1113957di this study proposesfuzzy evaluation values for the materials disassembled fromwaste furniture 2 for the product damage degree (quite

worn-out) 2 for repair feasibility (low reparability) and 2for market demand (relatively low) )erefore the fuzzyvalue of 1113957di is inferred as 1113957d 0027

1113957d f μ1113957d(a) μ1113957d

(t) μ1113957d(m)1113874 1113875

(054 minus 045)(054 minus 045)(037 minus 025)

0036 0027 (21)

362 Establishment of Fuzzy Information 1113957ui and 1113957viFirst define the three fuzzy inputs as environmental pro-tection laws and regulations environmental performanceindexes and the product market demand

(i) )e membership function for environmental pro-tection laws and regulations is no relevant laws andregulations low ratio average relatively high ratiostrict regulations )e trigonometric function for itis μ1113957u(p) [035 075]

(ii) )e membership function for the environmentalperformance index is extremely high impact indexrelatively high impact index average relatively lowimpact index extremely low impact index )etrigonometric function for it is μ1113957u(n) [025 075]

(iii) )e membership function for the product marketdemand is extremely low relatively low averagerelatively high extremely high )e trigonometricfunction for it is μ1113957u(m) [045 085]

)e fuzzy functions for 1113957ui and 1113957vi are as follows

1113957u f μ1113957u( ( p) μ1113957u(n) μ1113957u(m)

0 if plt 035 or nlt 025 or mlt 045

(p minus 035)(n minus 025)(m minus 045)

008 if 075gtpge 035 and 075gt nge 025 and 085gtmge 045

(p minus 035)(n minus 025)

02 if 075gtpge 035 and 075gt nge 025 andmge 085

(n minus 025)(m minus 045)

02 if pge 075 and 075gt nge 025 and 085gtmge 045

(p minus 035)(m minus 045)

016 if 075gtpge 035 and nge 075 and 085gtmge 045

n minus 02505

if pge 075 and 075gt nge 025 andmge 085

p minus 03504

if 075gtpge 035 and nge 075 andmge 085

m minus 04504

if pge 075 and nge 075 and 085gtmge 045

1 if pge 075 and nge 075 andmge 085

⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩


1113957v f μ1113957v(p) μ1113957v(n) μ1113957v(m)( 1113857

0 if plt 035 or nlt 025 ormlt 045









n minus 02505


p minus 03504


m minus 04504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(22)

Calculation of fuzzy information 1113957ui this study proposesfuzzy evaluation values for reusable materials from coarselycrushed furniture 3 for environmental protection rules andregulations (ordinary) 3 for environmental performance

index (average impact index) and 4 for product marketdemand (relatively high) )erefore the fuzzy value of 1113957ui isinferred as 1113957u 018

1113957u f μ1113957u(p) μ1113957u(n) μ1113957u(m)( 1113857 (055 minus 035)(055 minus 025)(069 minus 045)

008 018 (23)

Calculation of fuzzy information of 1113957vi this study pro-poses fuzzy evaluation values for reusable materials fromfinely crushed furniture 3 for environmental protectionrules and regulations (ordinary) 3 for the environmental

performance index (average impact index) and 4 forproduct market demand (relatively high) )erefore thefuzzy value of 1113957vi is inferred as 1113957v 018

1113957v f μ1113957v(p) μ1113957v(n) μ1113957v(m)( 1113857 (055 minus 035)(055 minus 025)(069 minus 045)

008 018 (24)

363 Calculation of Fuzzy Values )e fuzzy value reflectsthe actual proportion of the waste furniture that was put toreuse [36] )ere were a total of four fuzzy values in thisstudy the proportion of waste furniture used in repair 1113957Xithe proportion of waste furniture disassembled for reuse1113957Di the proportion of waste furniture coarsely crushed forreuse 1113957Ui and the proportion of waste furniture finelycrushed for reuse 1113957Vi In the previous section some fuzzyvalues were set to reflect the factors that influenced theproduction programming for waste furniture in Taiwanand the membership functions that reflected the reuse ofwaste furniture through the fuzzy theory were established

Furthermore it was necessary to calculate the corre-sponding proportions of the fuzzy information to theactual production programming for waste furniture sothat relevant production planning could be performed)e proportions could be solved through the interpolationof fuzzy information the fuzzy information between theknown maximum and minimum proportions for pro-duction planning was substituted to determine the pro-portion )e equation sets x as the known number todetermine the value of the linear function y(x) and (x1 y1)and (x2 y2) as the maximum and minimum valuesrespectively


y minus y1( 1113857

x minus x1( 1113857

y2 minus y1( 1113857

x2 minus x1( 1113857 (25)

y y2 minus y1( 1113857

x2 minus x1( 11138571113890 1113891 x minus x1( 1113857 + y1 (26)

)e right side of equation (21) was the known x valueand a constant Accordingly y(x) could be obtained Usingthe current situation in Taiwan as an example from theexpert opinions on fuzzy information 1113957xi could be initiallydetermined to be 0105 1113957di 0036 1113957ui 018 and 1113957vi 018Furthermore 1113957Xi

1113957Di1113957Ui and 1113957Vi could be obtained through

the interpolation method )e ratio of 1113957Xi was between 10and 30 1113957Di between 5 and 15 1113957Ui between 35 and 45and 1113957Vi between 35 and 45 )rough the interpolationmethod the values for 1113957Xi

1113957Di1113957Ui and 1113957Vi were calculated as

follows 1113957Xi 0121 1113957Di 00536 1113957Ui 0368 and 1113957Vi 0368

4 Results

)is study made comparisons between simulated situationsand conducted a performance evaluation and sensitivityanalysis regarding the C2C production programming modelfor waste furniture )e simulated situations were writtenusing the programming language in the Matlab R2010aversion and the simulation was executed on the ASUS A52J213G CUP computer For each situation 30 groups of datawere used to perform experiments

41 Situation Analysis

411 Parameter Settings for the Waste Furniture RecyclingCenter

(i) )e amount of recycled waste furniture the wastefurniture data collected from the center are shownin Table 1 For each batch the output of remanu-factured furniture the amount of materials dis-assembled from waste furniture and the amount ofmaterials from crushed furniture were randomlychosen under the constraint of the maximumoutput )e simulation was performed throughrandomly generated numbers as the outputs

(ii) Prices of various products this study utilized theprofits of a waste furniture remanufacturing centerin 2006 which were from the sales of remanu-factured furniture when it calculated the unit priceof remanufactured furniture )e annual salesrevenue of remanufactured furniture was NTD687428 yuan and the annual volume was 455592metric tons )us the average revenue of a ton ofremanufactured furniture was estimated to beNTD 1508868 yuan )e crushed materials couldbe divided into coarsely and finely crushed Huangand Liu pointed out that the price of a metric ton ofcoarsely crushed material is NTD 700 yuan whilethe price of finely crushed material is NTD 1000yuan

(iii) Various relevant costs various costs were calculatedbased on the relevant cost data provided by theTEPA and Liu )e results were as follows theaverage cost of waste furniture removal was NTD16667metric ton the average cost of repairingwaste furniture was NTD 144524metric ton theaverage cost of disassembling reusable parts fromwaste furniture was NTD 35764metric ton theaverage cost of new materials was NTD 52679metric ton the average cost of coarsely crushingwaste furniture was NTD 400metric ton and theaverage cost of finely crushing waste furniture wasNTD 600metric ton

(iv) Capacity limitations this study assumed that therewere four repairers namely two workers whodisassembled waste furniture and two workers whooperated the crusher Each person worked 8 hoursper day and each month had 22 working daysSuppose for example it took the workers a monthto process a batch then the workers would have 704hours to repair each batch of waste furniture 352hours to disassemble it and 352 hours to crush it asshown in Table 2

412 Situational Simulation

(i) Taiwan has continuously promoted relevant recy-cling programs to encourage the recycling and reuseof waste furniture such as the ldquoRecycling Programfor General Waste Resourcesrdquo Due to the differ-ences in urban and rural living habits in Taiwan thediscarded waste furniture collected from urban andrural areas is in different states Taiwan currently hasgood repair techniques for waste furniture How-ever the current demand for remanufactured fur-niture is still low

(ii) Germany promulgated a decree on recycling wastewood which is called the ldquoOrdinance on theManagement of Waste Woodrdquo )is decree pro-hibits the casual disposal of waste wood furniture[37 38] and divides the recycled wood into fivecategories )ere are different ways of processingand reusing waste wood depending on the category

(iii) China (Ching-Tao) with the increasing awarenessof environmental protection waste furniture andwood recycling agencies have been established

Table 1 )e amount of recycled waste furniture for each month

Months )e amount (ton)January 2506February 196318March 20699April 224727May 24134June 523495July 573403August 971177


throughout China )ere are also relevant rules andregulations in guiding the reuse of waste furnitureand wood Although there have been successfulcases and policy support overall recycling wastefurniture and wood has not been widely promotedin China

)e fuzzy information in this study varied with differentsituations and the fuzzy information is collated as shown inTable 3 )e setting of parameters for the C2C waste fur-niture production programming model reflected the factthat Germany had the greatest potential of reusing wastefurniture followed by Taiwan and China

)rough the PSO the maximum profit and the pro-duction planning amount of the 30 groups for each situationwere obtained )e average maximum profit and planningproduction volume of the 30 groups for each situation areshown in Table 4

42 Performance Evaluation

(i) Evaluation of statistical optimization this evalua-tion was done to verify whether the programmingmodel and algorithm proposed in this study werethe optimal solution )e 30 entries of data for eachsituation were used for the statistical optimizationevaluation )e Weibull++8 software was used asthe analytical tool )e statistical optimization andthe application of the software were described ac-cordingly [39] )e proposed PSO had variouscombinations of the data which were consistentwith Weber distribution in different situations )etest statistics were all less than P value as 001 andthe solutions obtained by each combination fellwithin the optimal prediction interval According tothe analytical results above the PSO proposed inthis study had a good solution quality and perfor-mance under various environmental combinationsFrom the perspective of statistical optimization itcould also prove that the results obtained in thisstudy were the optimal solution

(ii) Analysis of simulation results the simulation resultswere used to conduct ANOVA )e results showedthat there were significant differences in profit fromdifferent situations under waste furniture C2Cproduction programming After that multiplecomparisons were made to discover the difference

between situations in different degrees of fuzzyinformation )e comparison of the profits revealedthat there were significant differences between eachof the three situations namely Taiwan Germanyand China (Ching-Tao City) since the P value was001 which was less than 005)e aforesaid analysisindicated that different degrees of fuzzy informationexerted an impact on the results of the C2C pro-duction programming Germany with its highproductivity obtained the maximum profit whileChina (Ching-Tao City) received the lowest profitamong the three situations )us it was verifiedthat with the programming model the maximumprofit and production in different situations couldbe planned

(iii) Sensitivity analysis the current average unit costfor repairing furniture was NTD 144542 yuanwhich was expected to be reduced in the currentsituation )erefore this study discussed thesensitivity analysis of the repair cost of wastefurniture and the cost of disassembling wastefurniture for reusable materials )is study ex-plored the changes when the repair cost was re-duced from the original unit repair cost of NTD1445 yuan to 1350 yuan 1250 yuan 1150 yuanand 1050 yuan respectively With the cost ofrepairing furniture decreasing the sales obviouslydecreased but there was no significant differencein the output of remanufactured furniture and theutilization of crushed materials However if morecrushed materials from waste furniture were usedthere would be a higher profit )erefore even ifthe waste furniture was damaged and even beyondrepair it should also be recycled not only to reducethe amount of garbage but also to maximize thevalue of the resources

43 Strategies to Improve the Benefits of Recycling WasteFurniture

431 Compulsory Procurement of the Authorities Wastefurniture recycling and reuse along with the economicbenefits of recycling and reusing waste furniture in Taiwanhas been constantly reviewed )erefore this study proposesthe following strategies to improve the benefits from recy-cling waste furniture

Table 2 )e processing capacity for a unit of time

Categories of time available Time

)e amount of repaired waste furniture for a unit of time 1200 tonstimes 20 240 tons240 tonsdivide 704 034 tonshour

)e amount of disassembled waste furniture for a unit of time 1200 tonstimes 10 120 tons120 tonsdivide 352 hours 034 tonshour

)e amount of coarsely crushed waste furniture for a unit of time 1200 tonstimes 30 360 tons360 tonsdivide 352 hours 1023 tonshour

)e amount of finely crushed waste furniture for a unit of time 1200 tonstimes 30 360 tons360 tonsdivide 352 hours 1023 tonshour


)is study proposes that furniture procurement by theauthorities should be regulated )e suggestion is that itbecomes compulsory for the authorities to purchaseremanufactured furniture and their purchase volumewould therefore reach 10 of their total annual purchasesof furniture According to data gathered from the TaiwanBuying Network the total budget for furniture-relatedprocurement by the authorities in Taiwan in July 2013reached NTD 100864705 yuan If 5 constitutes the rev-enue of remanufactured furniture sales the amount is NTD5043235 yuan )e average benefit earned from a ton ofrecycled furniture is estimated to be NTD 1508868 yuanbased on this study To reap the profit of NTD 5043235yuan at least 3342 tons of remanufactured furniture(5043235 divided by 1508868) is needed in order to meetthe demand of the authorities According to the report onthe implementation of the BulkyWaste Recycling and Reuseprogram by the Bureau of Environmental Inspection [40] itis feasible to produce at least 3342 tons of remanufacturedfurniture permonth)is strategy can provide the benefits asfollows

(i) Economic benefits if it is compulsory for the au-thorities to purchase remanufactured furniture theaccumulated revenue will reach NTD 40345880yuan in eight months Compared with the estimated431470 yuan which is eight monthsrsquo profits ofremanufactured furniture sales for a county theamount is 93 times over Obviously the economicbenefit is considerable

(ii) Garbage reduction and increased reuse of wastefurniture the average profit of one ton of rema-nufactured furniture is estimated to be NTD1508868 yuan)erefore to gain the profit of NTD40345880 yuan from remanufactured furnituresales the furniture industry needs to produce atleast 26736 tons of remanufactured furniture

(iii) Carbon dioxide reduction according to the reporton recycling and reuse of waste furniture nation-wide by the TEPA in July 2011 the recycling ofwaste wood per kilogram can reduce the emission ofcarbon dioxide by approximately 30 kg In thisstudy 318005 metric tons of waste furniture wererecycled thereby reducing 9564150 metric tons ofcarbon dioxide emissions If it is compulsory for theauthorities to buy remanufactured furniture theamount of waste furniture to be repaired increasesto 26736 metric tons reducing 80208000 metrictons of carbon dioxide emissions Obviously agreater environmental benefit can be achieved if thestrategy is implemented (Table 5)

432 Subsidy Policy )is study suggests that a subsidy beprovided to encourage the recycling of waste furniture Fromthe information compiled by the TEPA [1] the disposal costfor a ton of general garbage is NTD 1811 yuan on average Ifthe NTD 1811 yuan is applied to the recycling of wastefurniture in order to increase the reuse of waste furniture it

is estimated that NTD 100 yuan can be used to subsidize therecycling of a waste table and 12 for the recycling of a wastechair Suppose for example that the subsidy policy canincrease 10 of recycled waste furniture the potentialbenefits for implementing the subsidy policy are as follows

(i) Economic benefit in comparison with the expectedprofit of NTD 431470 yuan for eight monthsrsquo worthof remanufactured furniture in a county the totalrevenue can reachNTD 4735893 yuan if the subsidypolicy is implemented with an additional profit ofNTD 421193 yuan Evidently the subsidy policycan further improve the economic benefit

(ii) Carbon dioxide reduction the recycling of wastewood per kilogram can reduce carbon dioxideemissions by approximately 30 kilograms In thisstudy the amount of recycled waste furnitureoriginally planned for 8 months in a county is318005 metric tons )e amount is expected toincrease by 10 if the subsidy policy is implementedie 350686 metric tons Under this circumstancethe carbon dioxide emissions can be reduced by10520580 metric tons and 956430 tons morecompared with the original reduction of 9564150metric tons Consequently the subsidy policy ispredicted to have an exceptional environmentalprotection benefit

433 Corporate Social Responsibility Table 6 presents thetop 50 prestigious firms in Taiwan recycle their waste officefurniture when they need replacements In addition no lessthan 1 of the newly procured office furniture should beremanufactured furniture )rough the implementation ofthis strategy top firms can contribute their efforts to en-vironmental protection In this way the amount ofreclaimed waste furniture and the corresponding values isimproved If the remanufactured furniture bought by topfirms reaches 1 of their newly procured equipment theincurred benefits are as follows

(i) Economic benefits suppose 5 of their expenditureon office equipment is used to purchase remanufac-tured furniture then the firms spendNTD 33640790yuan in one year In this way the profit fromremanufactured furniture sales in eight months willreach NTD 22427193 yuan )is strategy is expectedto increase profits 52 times Evidently this strategy hasthe potential to bring considerable economic profitscompared with the original profit of NTD 431470yuan for a county in 8months as shown in Table 7

(ii) Garbage reduction and improvement on recyclingwaste furniture it is necessary to produce approxi-mately 14864 tons of remanufactured furniture forthe firms to procure remanufactured furniture to reapa profit of NTD 22427193 yuan from the remanu-factured furniture business To this end a largeamount of waste furniture needs to be collected)erefore it is necessary to promote the recycling ofwaste furniture In addition to top firms the


authorities also need to actively promote the recyclingof waste furniture )rough the implementation ofthis strategy it is bound to improve the benefits ofrecycling waste furniture and reduce garbage

(iii) Carbon dioxide reduction the recycling of wastewood per kilogram can reduce the carbon dioxideemissions by approximately 30 kilograms Cur-rently 388005 metric tons of waste furniture isrecycled thereby reducing carbon dioxide (CO2)emissions of 9564150 metric tons If strategy three

is implemented it is expected to cause a reduction of44592000 metric tons of CO2 emissions and14864 tons of recycled furniture would need to berepaired)erefore this strategy is certain to furtherenhance the environmental protection benefits aspresented in Table 8

)is study compares and evaluates the performance ofthe waste furniture C2C production programming modelthat has been proposed As a result the current situation inTaiwan has been highlighted and production for Taiwan

Table 5 )e comparison of benefits between the current situation and strategy one

Benefits Current situation Strategy 1 )e improved benefit)e amount of recycled furniture 431470 40345880 An increase in 10 recycled furnitureProfit 318805 26736 An increase in NTD 421193 yuanCO2 reduction (ton) 9564150 80208000 A decrease in 956430 tons of CO2

Table 6 )e comparison of benefits between the current situation and strategy two


Table 7 )e benefits of top firms purchasing remanufactured furniture

)e most prestigious firms in Taiwanin 2012

)e expenditure on office furniture andequipment in 2012

)e profit from purchasing remanufactured productswith the 1 cost of office equipment

1 Taiwan SemiconductorManufacturing Firm $3348864000 $33488640

2 Uni-President Firms Corporation $287000 $28703 Giant Manufacturing Co Ltd $1911000 $19110

4 Synnex Technology InternationalCorporation [41] $491000 $4910

5 Delta Electronics $12526000 $125260)e sum of the profits from remanufactured furniture sales $33640790

Table 3 )e comparison of fuzzy information in different situations

Fuzzy information situations 1113957xi1113957di 1113957ui 1113957vi

Taiwan 0105 0027 018 018Germany 0252 00006 0648 0648Ching-Tao China 0005 00013 0003 0003

Table 4 )e results for the C2C waste furniture production programming in different situations

Situations andresults

Maximumprofits

Output of remanufacturedfurniture

)e output of coarsely crushedfurniture

)e output of finely crushedfurniture

Taiwan $431470 431 1554 1560Germany $499757 297 1779 1786Ching-Tao China $390789 604 1427 1431Unit metric ton


Germany and China has been planned It has been foundthat different degrees of fuzzy information have an impacton C2C production planning )erefore the C2C produc-tion programming model can assist the waste furnitureremanufacturing center by effectively carrying out the planof waste furniture reuse to achieve the maximum profit

5 Concluding Remarks

)is study established the C2C waste furniture productionprogramming model )e fuzzy theory was used to definethe degree of product damage the technical feasibility etcIn this way the optimal outputs of remanufactured furni-ture coarsely crushedmaterials and finely crushedmaterialsfor production programming were derived )e maximumprofit for remanufactured furniture sales was also obtained)e situational simulations revealed that the qualitativeinformation proposed had a significant impact on C2Cwastefurniture production programming )is study demon-strated through the statistical optimization and one-wayanalysis of variance that the results from different situationswere optimal solutions In this way it was verified that theC2C production programming model could be used toobtain the maximum profit )is study filled the gaps fromprior studies [9 11]

In practice this study proposed three strategies (a) theauthorities are obligated to buy a certain proportion ofremanufactured furniture to newly produced furniture (b)incentives should be given to encourage recycling wastefurniture and (c) firms are obliged to purchase remanu-factured furniture as office furniture )ese three strategieswere analyzed to show that they had a strong potential toimprove the benefits and profits of recycling waste furnitureConsequently the recommendation was made that theauthorities adopt and implement these three strategiesAdditionally C2C waste furniture production planning wasexplored by focusing on the waste furniture recycling centerIn the future planning done by the TEPA recycling plants intownships were also integrated to cause the resources toproduce more benefits )erefore the recommendation is toconsider how to better integrate the resources of recyclingplants in the future to further improve the benefits of theC2C waste furniture production programming

)e findings regarding the relevant attributes for mea-suring environmental loads can be further incorporated intoproduction programming to achieve sustainable develop-ment such as the benefits from wood furniture recycling Ifrelevant attributes are taken into account when productionprogramming is performed comprehensive benefits wouldbe achieved )is study has applied the 3Rs and proposes the3 strategic types compulsory procurement by the authori-ties subsidy policy and corporate social responsibility All

the strategies include the amount of recycled furnitureprofit and CO2 reduction at the same time )e compulsoryprocurement by the authorities is most effective in terms ofthe amount of recycled furniture profit and CO2 reductionthat occurs Hence this study recommends that the TEPAcreates regulation for the recycling process )is study alsorecommends that compulsory procurement by the au-thorities be based on the recycling subsidy proportion andon a higher recycling subsidy proportion with recycled greenproducts being produced

Data Availability

Data are available from the corresponding author for re-searchers who meet the criteria for access to confidentialdata

Conflicts of Interest

)e authors declare that they have no conflicts of interest

References

[1] Taiwan Environmental Protection Administration AnnualReport on Resource Recycling and Reuse Taiwan Environ-mental Protection Administration Taipei City Taiwan 2011

[2] Taiwan SemiconductorManufacturing Company Limited 2012Financial Report for Taiwan Semiconductor ManufacturingCompany Taiwan Semiconductor Manufacturing CompanyLimited Hsinchu Taiwan 2013

[3] C W R Lin S Y Jeng M L Tseng and R G Tan ldquoA cradle-to-cradle analysis in the toner cartridge supply chain usingfuzzy recycling production approachrdquo Management of En-vironmental Quality An International Journal vol 30 no 2pp 329ndash345 2018

[4] C-W Lin S-Y Jeng and M-L Tseng ldquoSustainable devel-opment for zero-wastewater-discharge reproduction planningunder quantitative and qualitative informationrdquoManagementof Environmental Quality An International Journal vol 30no 5 pp 1114ndash1131 2019

[5] M-L TsengM S Islam N Karia F A Fauzi and S Afrin ldquoAliterature review on green supply chain management trendsand future challengesrdquo Resources Conservation and Recyclingvol 141 pp 145ndash162 2019

[6] M S Lee M-L Tseng and N Karia ldquoAssessment of cor-porate culture in sustainability performance using a hierar-chical framework and interdependence relationsrdquo Journal ofCleaner Production vol 217 pp 676ndash690 2019

[7] C C Lao ldquoGlobal development strategies-new opportunitiesfor Taiwan-US Businessrdquo in Proceedings of the ModernEngineering Technology Symposium pp 9ndash11 Taipei TaiwanOctober 2018

[8] C M Su D J Horng M L Tseng A S F Chiu K J Wu andH P Chen ldquoImproving sustainable supply chain

Table 8 )e comparison of benefits between the current situation and strategy three



management using a novel hierarchical Grey-DEMATELapproachrdquo Journal of Cleaner Production vol 134 pp 469ndash481 2015

[9] M Fujii T Fujita S Ohnishi N Yamaguchi G Yong andH-S Park ldquoRegional and temporal simulation of a smartrecycling system for municipal organic solid wastesrdquo Journalof Cleaner Production vol 78 pp 208ndash215 2014

[10] C W Lin ldquo)e new challenges brought by the sustainabledevelopment of green logisticsrdquo Taiwan Logistics Yearbookpp 481ndash531 2008

[11] M-L Tseng R R Tan A S F Chiu C-F Chien andT C Kuo ldquoCircular economy meets industry 40 can big datadrive industrial symbiosisrdquo Resources Conservation andRecycling vol 131 pp 146-147 2018

[12] R U Pandey A Surjan and M Kapshe ldquoExploring linkagesbetween sustainable consumption and prevailing greenpractices in reuse and recycling of household waste case ofBhopal city in Indiardquo Journal of Cleaner Production vol 173pp 49ndash59 2018

[13] E Tam K Soulliere and S Sawyer-Beaulieu ldquoManagingcomplex products to support the circular economyrdquo ResourcesConservation and Recycling vol 145 pp 124-125 2019

[14] Y Lin H-P Cheng M-L Tseng and J C C Tsai ldquoUsingQFD and ANP to analyze the environmental productionrequirements in linguistic preferencesrdquo Expert Systems WithApplications vol 37 no 3 pp 2186ndash2196 2010

[15] M Tseng M Lim andW PWong ldquoSustainable supply chainmanagementrdquo Industrial Management amp Data Systemsvol 115 no 3 pp 436ndash461 2015

[16] C H Chang ldquoResearch on integrated fuzzy recycling andproduction planning in the green supply chain managementrdquo)esis for Masterrsquos Degree National Yunlin University ofScience and Technology Douliu Taiwan 2005

[17] Y Zhong and P Wu ldquoEconomic sustainability environ-mental sustainability and constructability indicators related toconcrete- and steel-projectsrdquo Journal of Cleaner Productionvol 108 pp 748ndash756 2015

[18] T-D Bui F M Tsai M-L Tseng K-J Wu and A S ChiuldquoEffective municipal solid waste management capability un-der uncertainty in Vietnam utilizing economic efficiency andtechnology to foster social mobilization and environmentalintegrityrdquo Journal of Cleaner Production vol 259 Article ID120981 2020

[19] A Azapagic ldquoDeveloping a framework for sustainable de-velopment indicators for the mining and minerals industryrdquoJournal of Cleaner Production vol 12 no 6 pp 639ndash6622004

[20] M S Islam M-L Tseng and N Karia ldquoAssessing greensupply chain practices in Bangladesh using fuzzy importanceand performance approachrdquo Resources Conservation andRecycling vol 131 pp 134ndash145 2018

[21] L C Braat Modeling for Population and Sustainable Devel-opment Fee University London New York 1991

[22] L Cui K J Wu and M L Tseng ldquoExploring a novel agri-cultural subsidy model with sustainable development abenchmark Chinese agribusiness in Liaoningrdquo Sustainabilityvol 9 no 1 p 19 2017

[23] L Ma L Wang K-J Wu M-L Tseng and A S F ChiuldquoExploring the decisive risks of green development projects byadopting social network analysis under stakeholder theoryrdquoSustainability vol 10 no 6 p 2104 2018

[24] M-H Wong J Hu M-L Tseng A S F Chiu and C LinldquoSustainable development in technological and vocationalhigher education balanced scorecard measures with

uncertaintyrdquo Journal of Cleaner Production vol 120 no 1pp 1ndash12 2016

[25] X Xu Y Wang and L Tao ldquoComprehensive evaluation ofsustainable development of regional construction industry inChinardquo Journal of Cleaner Production vol 211 pp 1078ndash1087 2019

[26] K P Nurjanni M S Carvalho and L Costa ldquoGreen supplychain design a mathematical modeling approach based on amulti-objective optimization modelrdquo International Journal ofProduction Economics vol 183 pp 421ndash432 2017

[27] A A M Sultan E Lou and P T Mativenga ldquoWhat should berecycled an integrated model for product recycling desir-abilityrdquo Journal of Cleaner Production vol 154 pp 51ndash602017

[28] Capital Engineering Corp A comprehensive Report onMainland Chinarsquos Resource Recycling Market Capital Engi-neering Corp New Delhi India 2010

[29] W-P Wong Q Deng M-L Tseng L-H Lee andC-W Hooy ldquoA stochastic setting to bank financial perfor-mance for refining efficiency estimatesrdquo Intelligent Systems inAccounting Finance and Management vol 21 no 4pp 225ndash245 2014

[30] J Kennedy and R C Eberhart ldquoParticle swarm optimizationrdquoin Proceedings of the IEEE International Conference on NeuralNetworks 4 pp 1942ndash1948 Perth Australia December 1995

[31] G J Klir and B Yuan Fuzzy Sets and Fuzzy Logic 5eory andApplication Prentice-Hall Upper Saddle River NJ USA1995

[32] W-W Wu Y-T Lee M-L Tseng and Y-H Chiang ldquoDatamining for exploring hidden patterns between KM and itsperformancerdquo Knowledge-Based Systems vol 23 no 5pp 397ndash401 2010

[33] J M Cadenas and J L Verdegay ldquoUsing fuzzy numbers inlinear programmingrdquo IEEE Transactions on Systems Man andCybernetics Part B (Cybernetics) vol 27 no 6 pp 1016ndash10221997

[34] C H Cheng ldquoA new approach for ranking fuzzy numbers bydistance methodrdquo Fuzzy Sets and Systems vol 95 pp 307ndash317 1998

[35] E H Chiu and S Assilian ldquoAn experiment in linguisticsynthesis with a fuzzy logic controllerrdquo International Journalof Man-Machine Studies vol 7 no 1 pp 1ndash13 1975

[36] H J Zimmermann Fuzzy Set 5eory and its ApplicationsSpringer Dordrecht Netherlands 2nd edition 1991

[37] H F Huang and C H Liu Recycling Economy in GermanyChina Science Publishing amp Media Ltd Beijing China 1stedition 2009

[38] J F D Tapia M A B Promentilla M-L Tseng and R R TanldquoScreening of carbon dioxide utilization options using hybridanalytic hierarchy process-data envelopment analysismethodrdquo Journal of Cleaner Production vol 165 pp 1361ndash1370 2017

[39] I H Chen 5e Two-Stage Dependency Scheduling for theAvailability of Suppliers and Machines of National YunlinUniversity of Science and Technology )esis for MasterrsquosDegree National Yunlin University of Science and Tech-nology Douliu Taiwan 2007

[40] )e Bureau of Environmental Inspection Report on theImplementation of the Bulky Waste Recycling and Reuse )eBureau of Environmental Inspection Taipei City Taiwan 2011

[41] Synnex Technology International Corporation (STIC) 2011and 2012 Financial Report for Synnex Technology InternationalCorporation Synnex Technology International Corporation(STIC) Hong Kong China 2013


serve as the raw material of newly produced items and thatstep in the manufacturing process would comply with en-vironmental protection laws and regulations to reduce re-source consumption and harmful emissions In this waysustainability could be achieved [6ndash8] Moreover customerswould now pay closer attention to whether products thatwere at the end of their useful life were to be disposed ofrecycled or reused due to environmental protectionawareness It has been discarded ldquowastesrdquo can be recycledreduced and reused (3Rs) and be more valuable [9ndash11]

In the literature Fujii et al [9] discussed the demand forrecycled products economic conditions weight reductionproduct reuse and quantity and types of competitiverecycled products they developed a social system for cus-tomer purchases that influence waste generation Pandeyet al [12] promoted reuse and recycling practices in reducingwastes and analyzed the practices that help in reducing thegeneration of waste Tseng et al [11] indicated that there wasinterdependence and interrelationships among the attri-butes along with a lack of operational data-driven andoptimization solutions in supply chain networks to optimizeefficiency Tam et al [13] proposed waste materials needed tobe efficiently returned for production and the time-testedprocesses of reuse recovery and recycling (3Rs) were es-sential )e attributes were usually developed from quali-tative information and quantitative data were used indecision-making However prior studies did not explainhow the attributes worked together to enhance the demandfor recycled products and such studies ignored the way theattributes were qualitative in measure and used onlyquantitative data [4 14 15] In addition there was a need toanalyze the 3Rs in the optimization solution

However bulky waste is difficult to collect and removeregularly )ere is no complete recycling system and theresources are not used effectively With the promotion ofrelevant recycling programs bulky waste such as wastefurniture that still has value is repaired and reused In thisway the bulky waste as well as the environmental loads canbe effectively reduced an effect which is conducive to thegoal of zero waste disposal )e fuzzy set theory deals withqualitative information It is arguable that bulky waste is away to generate profit in the value chain [8 16 17] Hencefor this study production programming is expected forwaste furniture so that the maximum reuse rate can beachieved)erefore this study aims to establish the model ofreusing the waste furniture to obtain the maximum profitfrom waste product sales )is study has established the C2Crecycling production planning model for waste furniturethrough a mathematical model It is hoped that with thismodel waste furniture is effectively recycled and reusedrecycling profit can be maximized and optimal remanu-facturing volume is obtained [18] In addition this study hasprovided situational simulations to verify the optimality ofthe model

)is study focuses on waste furniture recycling andremanufacturing the furniture through recycling centersunder the TEPA jurisdiction includes the cleaning teamsthat are responsible for removing and transporting wastefurniture as well as the processing centers in which waste

furniture is processed for reuse and remanufacturing In theprocessing centers reusable waste furniture is repairedreusable parts are disassembled and the parts beyond repairare crushed )is study takes into account the followingcosts recycling cost repair cost disassembly cost andcrushing cost )e study does not consider the inventorycost For the purchase cost only the cost of new raw ma-terials is taken into consideration

)e rest of this study is organized as follows Section 2 isthe theoretical background method and industrial back-ground are described in Section 3 Section 4 presents theresults and the sensitivity analysis lastly the concludingremarks are discussed

2 Literature Review

Sustainable development was first proposed by the WorldCommission on Environment and Development of theUnited Nations (1987) )is proposal aimed to meet theneeds of the present without compromising the ability offuture generations to meet their own needs [19 20] Inaddition Braat [21] proposed that sustainable develop-ment should include three principles ie fairness sus-tainability and commonality and economic developmentshould be pursued based on the sustainable developmentof the ecological environment and promoted around theworld [10 22 23] Wong et al [24] used sustainable de-velopment assessment to achieve social environmentaland economic benefits and created an assessment modelusing qualitative information and quantitative dataHowever sustainable development included recyclingend-of-life products while the planning and performanceevaluation of recycling end-of-life product plans ensuredthat collected recyclable materials as well as the assess-ment of environmental impacts did not increase thoseimpacts Xu et al [25] explored sustainable developmentdriving forces to assess sustainability in China In additionthe assessment of social environmental and economicbenefits was performed using qualitative and quantitativemeasures Prior studies were usually lacking in attributesanalysis

Lin et al [3] highlighted the clean cycle strategy andpresented better recycled product qualities and less dissi-pation of hazardous substances during recycled productusage )is study ignored CO2 emissions during therecycled production process Being free of hazardoussubstances was always required in the new productionmanufacturing process Nurjanni et al [26] presented amultiobjective optimization mathematical model to reducecosts and minimize environmental pollution through atrade-off between financial and environmental issuesHowever the business model is needed to balance thesocial economic and environmental impacts Sultan et al[27] presented the mixture of materials and the separationof materials that make up a product as a model of thedesirability of recycling end-of-life products Lin et al [4]developed a cradle-to-cradle fuzzy recycling productionplanning model for a green product using the failure modeand effects analysis technique along with the Taguchi



3 Method







xi d (t + 1) xi d(t) + vi d(t + 1)

(1)

















Consumers



Categorization


Coarsely and finely

crushing



Plantingtrees Ashes

The reuse demand

Repair

Sorting



reuse



Partial damage



WM2

WMi

Coarsely crushing

Finely crushing


WM1

DFMi

Disassemble

Repair

CMi

CrushCCMi

CFMi

RFi

RMPi

NMi

Vi


Ui

Xi

1

2

iũi vi

d ixi

Di





1113957Z 1113944N

i1PSGi + 1113944

N

i1RSUi

minus 1113944N


(2)



1113944

N

i1PSGi 1113944

N



(3)




1113944N

i1RSUi 1113944

N




(4)





1113944N

i1RCi 1113944

N



1113944N

i1DP Di 1113944

N



(6)




1113944N

i1DP Ci 1113944

N





1113944

N

i1BCCi 1113944

N



1113944N

i1BFCi 1113944

N





1113957Xi + 1113957Di + 1113957Ui + 1113957Vi le 1 (12)






(17)



















1113957x f μ1113957x(a) μ1113957x(t) μ1113957x(m)( 1113857










t minus 04503


a minus 04503


m minus 02504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

1113957d f μ1113957d(a) μ1113957d

(t) μ1113957d(m)1113874 1113875










t minus 04503


a minus 04503


m minus 02504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(19)






0036 0105 (20)



1113957d f μ1113957d(a) μ1113957d

(t) μ1113957d(m)1113874 1113875


0036 0027 (21)






1113957u f μ1113957u( ( p) μ1113957u(n) μ1113957u(m)










n minus 02505


p minus 03504


m minus 04504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩


1113957v f μ1113957v(p) μ1113957v(n) μ1113957v(m)( 1113857










n minus 02505


p minus 03504


m minus 04504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(22)




008 018 (23)




008 018 (24)




y minus y1( 1113857

x minus x1( 1113857

y2 minus y1( 1113857

x2 minus x1( 1113857 (25)

y y2 minus y1( 1113857







4 Results

































































Maximumprofits












Data Availability




References

















































3 Method







xi d (t + 1) xi d(t) + vi d(t + 1)

(1)

















Consumers



Categorization


Coarsely and finely

crushing



Plantingtrees Ashes

The reuse demand

Repair

Sorting



reuse



Partial damage



WM2

WMi

Coarsely crushing

Finely crushing


WM1

DFMi

Disassemble

Repair

CMi

CrushCCMi

CFMi

RFi

RMPi

NMi

Vi


Ui

Xi

1

2

iũi vi

d ixi

Di





1113957Z 1113944N

i1PSGi + 1113944

N

i1RSUi

minus 1113944N


(2)



1113944

N

i1PSGi 1113944

N



(3)




1113944N

i1RSUi 1113944

N




(4)





1113944N

i1RCi 1113944

N



1113944N

i1DP Di 1113944

N



(6)




1113944N

i1DP Ci 1113944

N





1113944

N

i1BCCi 1113944

N



1113944N

i1BFCi 1113944

N





1113957Xi + 1113957Di + 1113957Ui + 1113957Vi le 1 (12)






(17)



















1113957x f μ1113957x(a) μ1113957x(t) μ1113957x(m)( 1113857










t minus 04503


a minus 04503


m minus 02504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

1113957d f μ1113957d(a) μ1113957d

(t) μ1113957d(m)1113874 1113875










t minus 04503


a minus 04503


m minus 02504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(19)






0036 0105 (20)



1113957d f μ1113957d(a) μ1113957d

(t) μ1113957d(m)1113874 1113875


0036 0027 (21)






1113957u f μ1113957u( ( p) μ1113957u(n) μ1113957u(m)










n minus 02505


p minus 03504


m minus 04504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩


1113957v f μ1113957v(p) μ1113957v(n) μ1113957v(m)( 1113857










n minus 02505


p minus 03504


m minus 04504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(22)




008 018 (23)




008 018 (24)




y minus y1( 1113857

x minus x1( 1113857

y2 minus y1( 1113857

x2 minus x1( 1113857 (25)

y y2 minus y1( 1113857







4 Results

































































Maximumprofits












Data Availability




References


















































Consumers



Categorization


Coarsely and finely

crushing



Plantingtrees Ashes

The reuse demand

Repair

Sorting



reuse



Partial damage



WM2

WMi

Coarsely crushing

Finely crushing


WM1

DFMi

Disassemble

Repair

CMi

CrushCCMi

CFMi

RFi

RMPi

NMi

Vi


Ui

Xi

1

2

iũi vi

d ixi

Di





1113957Z 1113944N

i1PSGi + 1113944

N

i1RSUi

minus 1113944N


(2)



1113944

N

i1PSGi 1113944

N



(3)




1113944N

i1RSUi 1113944

N




(4)





1113944N

i1RCi 1113944

N



1113944N

i1DP Di 1113944

N



(6)




1113944N

i1DP Ci 1113944

N





1113944

N

i1BCCi 1113944

N



1113944N

i1BFCi 1113944

N





1113957Xi + 1113957Di + 1113957Ui + 1113957Vi le 1 (12)






(17)



















1113957x f μ1113957x(a) μ1113957x(t) μ1113957x(m)( 1113857










t minus 04503


a minus 04503


m minus 02504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

1113957d f μ1113957d(a) μ1113957d

(t) μ1113957d(m)1113874 1113875










t minus 04503


a minus 04503


m minus 02504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(19)






0036 0105 (20)



1113957d f μ1113957d(a) μ1113957d

(t) μ1113957d(m)1113874 1113875


0036 0027 (21)






1113957u f μ1113957u( ( p) μ1113957u(n) μ1113957u(m)










n minus 02505


p minus 03504


m minus 04504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩


1113957v f μ1113957v(p) μ1113957v(n) μ1113957v(m)( 1113857










n minus 02505


p minus 03504


m minus 04504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(22)




008 018 (23)




008 018 (24)




y minus y1( 1113857

x minus x1( 1113857

y2 minus y1( 1113857

x2 minus x1( 1113857 (25)

y y2 minus y1( 1113857







4 Results

































































Maximumprofits












Data Availability




References

















































1113957Z 1113944N

i1PSGi + 1113944

N

i1RSUi

minus 1113944N


(2)



1113944

N

i1PSGi 1113944

N



(3)




1113944N

i1RSUi 1113944

N




(4)





1113944N

i1RCi 1113944

N



1113944N

i1DP Di 1113944

N



(6)




1113944N

i1DP Ci 1113944

N





1113944

N

i1BCCi 1113944

N



1113944N

i1BFCi 1113944

N





1113957Xi + 1113957Di + 1113957Ui + 1113957Vi le 1 (12)






(17)



















1113957x f μ1113957x(a) μ1113957x(t) μ1113957x(m)( 1113857










t minus 04503


a minus 04503


m minus 02504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

1113957d f μ1113957d(a) μ1113957d

(t) μ1113957d(m)1113874 1113875










t minus 04503


a minus 04503


m minus 02504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(19)






0036 0105 (20)



1113957d f μ1113957d(a) μ1113957d

(t) μ1113957d(m)1113874 1113875


0036 0027 (21)






1113957u f μ1113957u( ( p) μ1113957u(n) μ1113957u(m)










n minus 02505


p minus 03504


m minus 04504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩


1113957v f μ1113957v(p) μ1113957v(n) μ1113957v(m)( 1113857










n minus 02505


p minus 03504


m minus 04504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(22)




008 018 (23)




008 018 (24)




y minus y1( 1113857

x minus x1( 1113857

y2 minus y1( 1113857

x2 minus x1( 1113857 (25)

y y2 minus y1( 1113857







4 Results

































































Maximumprofits












Data Availability




References
















































1113944

N

i1BCCi 1113944

N



1113944N

i1BFCi 1113944

N





1113957Xi + 1113957Di + 1113957Ui + 1113957Vi le 1 (12)






(17)



















1113957x f μ1113957x(a) μ1113957x(t) μ1113957x(m)( 1113857










t minus 04503


a minus 04503


m minus 02504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

1113957d f μ1113957d(a) μ1113957d

(t) μ1113957d(m)1113874 1113875










t minus 04503


a minus 04503


m minus 02504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(19)






0036 0105 (20)



1113957d f μ1113957d(a) μ1113957d

(t) μ1113957d(m)1113874 1113875


0036 0027 (21)






1113957u f μ1113957u( ( p) μ1113957u(n) μ1113957u(m)










n minus 02505


p minus 03504


m minus 04504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩


1113957v f μ1113957v(p) μ1113957v(n) μ1113957v(m)( 1113857










n minus 02505


p minus 03504


m minus 04504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(22)




008 018 (23)




008 018 (24)




y minus y1( 1113857

x minus x1( 1113857

y2 minus y1( 1113857

x2 minus x1( 1113857 (25)

y y2 minus y1( 1113857







4 Results

































































Maximumprofits












Data Availability




References
















































1113957x f μ1113957x(a) μ1113957x(t) μ1113957x(m)( 1113857










t minus 04503


a minus 04503


m minus 02504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

1113957d f μ1113957d(a) μ1113957d

(t) μ1113957d(m)1113874 1113875










t minus 04503


a minus 04503


m minus 02504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(19)






0036 0105 (20)



1113957d f μ1113957d(a) μ1113957d

(t) μ1113957d(m)1113874 1113875


0036 0027 (21)






1113957u f μ1113957u( ( p) μ1113957u(n) μ1113957u(m)










n minus 02505


p minus 03504


m minus 04504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩


1113957v f μ1113957v(p) μ1113957v(n) μ1113957v(m)( 1113857










n minus 02505


p minus 03504


m minus 04504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(22)




008 018 (23)




008 018 (24)




y minus y1( 1113857

x minus x1( 1113857

y2 minus y1( 1113857

x2 minus x1( 1113857 (25)

y y2 minus y1( 1113857







4 Results

































































Maximumprofits












Data Availability




References


















































0036 0105 (20)



1113957d f μ1113957d(a) μ1113957d

(t) μ1113957d(m)1113874 1113875


0036 0027 (21)






1113957u f μ1113957u( ( p) μ1113957u(n) μ1113957u(m)










n minus 02505


p minus 03504


m minus 04504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩


1113957v f μ1113957v(p) μ1113957v(n) μ1113957v(m)( 1113857










n minus 02505


p minus 03504


m minus 04504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(22)




008 018 (23)




008 018 (24)




y minus y1( 1113857

x minus x1( 1113857

y2 minus y1( 1113857

x2 minus x1( 1113857 (25)

y y2 minus y1( 1113857







4 Results

































































Maximumprofits












Data Availability




References
















































1113957v f μ1113957v(p) μ1113957v(n) μ1113957v(m)( 1113857










n minus 02505


p minus 03504


m minus 04504



⎧⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎨

⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎪⎩

(22)




008 018 (23)




008 018 (24)




y minus y1( 1113857

x minus x1( 1113857

y2 minus y1( 1113857

x2 minus x1( 1113857 (25)

y y2 minus y1( 1113857







4 Results

































































Maximumprofits












Data Availability




References
















































y minus y1( 1113857

x minus x1( 1113857

y2 minus y1( 1113857

x2 minus x1( 1113857 (25)

y y2 minus y1( 1113857







4 Results

































































Maximumprofits












Data Availability




References


































































































Maximumprofits












Data Availability




References






















































Data Availability




References
















































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