Innovative and practical issues of multi-criteria decision-making in the supply chain management

Innovative and practical issues of multi-criteria decision-making in the supply chain

management

Prof. Valerio SalomonSao Paulo State University, Brasil

www.feg.unesp.br/~salomon

Workshop AHP/ANPITA 2011

http://www.feg.unesp.br/~salomon



www.feg.unesp.br/~salomon 2

Innovative and practical issues of multi-criteria decision-making in the

supply chain management

11/10/2011

Outline of presentation

1. Conceptual background2. Validation of an MCDM method application3. Compatibility Indexes4. Supply chain management



Conceptual background

11/10/2011

Who won the Winter 2010 Olympics? A quest into priorities and rankings J. Multi-Crit. Decis. Anal. (Saaty, 2010)

Negotiating the Israeli–Palestinian controversy from a new perspectiveInt. J. Inf. Tech. Decis. (Saaty & Zoffer, 2011)

An innovative orders-of-magnitude approach to AHP-based mutli-criteria decision making: Prioritizing divergent intangible humane actsEur. J. Oper. Res. (Saaty & Shang, 2011)




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Who won the Winter 2010 Olympics?


IOC Gold Silver Bronze Total

Canada 14 7 5 26

Germany 10 13 7 30

United States 9 15 13 37

Norway 9 8 6 23

CNN Total Gold Silver Bronze

United States 37 9 15 13

Germany 30 10 13 7

Canada 26 14 7 5

Norway 23 9 8 6



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Medal Gold Silver Bronze Priority

Gold 1 2 2 50%

Silver 1 1 25%

Bronze 1 25%

1st row PrioritiesCAN

(14, 7, 5)USA

(10, 13, 7)

1, 2, 2 50%, 25%, 25% 10 11.5

1, 3, 3 60%, 20%, 20% 10.8 11.0

1, 3, 4 63%, 21%, 16% 11.12 10.90

1, 3, 9 68%, 23%, 9% 11.69 10.69

1, 9, 9 82%, 9%, 9% 12.54 9.91

CAN 28x8 USA. p-value = 0.000156282 < 0.0004



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Sport Average ticket price CAN USA1 Alpine Skiing (Women’s Downhill) CND 125 = .223 0 /0 .185 / .23

21 Bobsleigh (Women’s) CND 60 = .107 .089 / .098 .018 / .010

39 Figure Skating (Ice Dance – Mixed) CND 290 = .518 .259 / .352 .171 / .119

48 Ice Hockey (Men’s) CND 560 = 1 .500 / .680 .330 / .230

49 Ice Hockey (Women’s) CND 220 = .393 .196 / .267 .130 / .090

86 Speed Skating (Men’s Team Pursuit) CND 140 = .250 .125 / .170 .083 / .058

2.524 / 3.035 2.757 / 2.444

48% / 55% 52% / 45%

Priorities used to rank: ( 50%, 33%, 17% ) / (68%, 23%, 9%)

[email protected] / AHP

mailto:[email protected]



11/10/2011

The Summer 2016 Olympics hosted city decisionA Ranking Reversal case


City Round 3 Round 2 Round 1

Rio de Janeiro 66 (67%) 46 (48%) 26 (28%)

Madrid 32 (33%) 29 (31%) 28 (30%)

Tokyo - 20 (21%) 22 (23%)

Chicago - - 18 (19%)

98 95 94



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Negotiating the Israeli–Palestinian controversy




11/10/2011





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Criteria CJHP RC IS PB CRW HR SPT Priorities

Control Jerusalem & holy places 1 .19 9 0 .21 1.81 8 25%

Refugee compensation…. 5.38 1 .22 0 7.74 5.73 1.68 25%

Increasing security .11 4.47 1 0 .33 8 7 19%

Permanent boarders 0 0 0 1 0 0 0 0%

Controlling & rationing of water 4.72 .13 3 0 1 5 .14 16%

Human rights .55 .17 .13 0 .20 1 .14 2%

Settlements in Palestinian territory .13 .60 .14 0 7 7 1 13%

Comparisons of the criteria for Israeli’s benefits from Palestinian concessions



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Ratings scale for concession evaluation

Excellent 1.0

Very high 0.9

High 0.8

Medium 0.7

Low 0.5

Very low 0.4

Negligible 0.3



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Israeli’s benefits from Palestinians’ concessions

Concession CJHP(25%)

RC(25%)

IS(19%)

PB(0%)

CRW(16%)

HR(2%)

SPT(13%) Total Ideal

Accept two-state solution VL E E N M .680 .736

Acceptance of noncontiguousState

N E E N N .605 .655

Acknowledge Israel’s existenceas a Jewish state

E E E VH M .924 1

Agree to compromise todemand of right of no return

H E E N VH .917 .992

… … … … … … … … … …



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Retributive function

𝐴′ 𝑠𝑟𝑎𝑡𝑖𝑜=𝐺𝑎𝑖𝑛𝑡𝑜 𝐴 𝑓𝑟𝑜𝑚𝐵′ 𝑠𝑐𝑜𝑛𝑐𝑒𝑠𝑠𝑖𝑜𝑛

𝐴′ 𝑠 𝑝𝑒𝑟𝑐𝑒𝑝𝑡𝑖𝑜𝑛𝑜𝑓 𝐵′ 𝑠𝑔𝑎𝑖𝑛 𝑓𝑟𝑜𝑚 𝐴′ 𝑠𝑐𝑜𝑛𝑐𝑒𝑠𝑠𝑖𝑜𝑛

𝐴′ 𝑠𝑟𝑎𝑡𝑖𝑜= ∑ (𝐴′ 𝑠𝑏𝑒𝑛𝑒𝑓𝑖𝑡𝑠×𝐵′ 𝑠𝑐𝑜𝑠𝑡𝑠) 𝑓𝑟𝑜𝑚𝐵′ 𝑠𝑐𝑜𝑛𝑐𝑒𝑠𝑠𝑖𝑜𝑛∑ (𝐵′ 𝑠𝑏𝑒𝑛𝑒𝑓𝑖𝑡𝑠×𝐴′ 𝑠𝑐𝑜𝑠𝑡𝑠) 𝑓𝑟𝑜𝑚 𝐴 ′ 𝑠𝑐𝑜𝑛𝑐𝑒𝑠𝑠𝑖𝑜𝑛

𝐵′ 𝑠𝑟𝑎𝑡𝑖𝑜=∑ (𝐵′ 𝑠 𝑏𝑒𝑛𝑒𝑓𝑖𝑡𝑠× 𝐴′ 𝑠𝑐𝑜𝑠𝑡𝑠) 𝑓𝑟𝑜𝑚 𝐴′ 𝑠 𝑐𝑜𝑛𝑐𝑒𝑠𝑠𝑖𝑜𝑛∑ (𝐴′ 𝑠𝑏𝑒𝑛𝑒𝑓𝑖𝑡𝑠×𝐵′ 𝑠𝑐𝑜𝑠𝑡𝑠 ) 𝑓𝑟𝑜𝑚𝐵 ′ 𝑠𝑐𝑜𝑛𝑐𝑒𝑠𝑠𝑖𝑜𝑛

≅ 1



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Matching concessions with corresponding gain/loss ratios in first meeting

Israeli’s Concessions Gain/Loss Palestinian’s Concessions Gain/Loss

Shared administration ofresources 1.03 Drop opposition to trade &

normal relations with Israel 1.03

Comply with UN resolutions

Right to economicDevelopment

7.27

Acceptance of noncontiguousstate

Incitement of anti-Israelisentiment in school

7.27

... ... ... ...



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Matching concessions with corresponding gain/loss ratios in second meeting

Israeli’s Concessions Gain/Loss Palestinian’s Concessions Gain/Loss

Adhere to International law

Right to education1083

Accept two-state solution(Israeli control of Jerusalem)

Adhere to International law1084

Comply with UN resolutions

Right to a free economy,economic development & Trade

461

Accept a demilitarized Palestinian state (not including Jerusalem)

End of incitement of anti-Israeli sentiment in School

457

... ... ... ...



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An innovative orders-of-magnitude approach




11/10/2011



www.feg.unesp.br/~salomon 2011/10/2011

Validation of Multi-criteria Decision-Making

1. Validation as a concept. Decision-making as a process

2. Performance of an MCDM method application3. Saaty’s, Garuti’s, and Salomon’s Compatibility

Indexes


Process OutputInput


Quality of the decision-making process


S I P O CDecision Making

Decision Aid or Decision Support

Validation of a decision

SIPOC (Suppliers, inputs, process, outputs, customers) is a Six Sigma tool. It was invented by Prof. Edwards Deming in the 1950’s, the legend goes.


Quality of the decision-making process


S I P O CCulture,

Environment, Interests, Law, etc.

Morita, H. Contribution to decision process analysis of unstructured problems. PhD dissertation. S. Paulo: USP, 2003 [In Portuguese].


Performance of an MCDM method application


S I P O C

Paula, D.C.; Salomon, V.A.P. Using indicators in the performance analysis of multiple criteria decision-making methods application. Proceedings of XL SBPO. J. Pessoa: SOBRAPO, 2007 [In Portuguese].

QQuantity of data

SCompatibility Index


Performance of an MCDM method application


eBAe TT

nS

2

1

Ni

i

ii nnQ1 2

)1(

Alternatives AHP* ANP* ANP** Actual

Kmart 18 % 25 % 23 % 26 %

Target 18 % 15 % 21 % 19 %

Wal-Mart 64 % 60 % 56 % 55 %

S 1.046 1.018 1.008

Q 95 334 771


Saaty’s and Salomon’s Compatibility indexes


𝑆=( 1𝑛2 )𝒆𝑇 [ 𝑥𝑖𝑥 𝑗 ]⦁ [ 𝑦 𝑖

𝑦 𝑗 ]𝒆𝑉=( 1𝑛2 )𝒆𝑇 ¿

Three compatible vectorsi xi yi zi order(xi, yi, zi)

1 .450 .490 .499 1

2 .300 .300 .300 2

3 .200 .200 .200 3

4 .050 .010 .001 4

S = 1.63 S = 2.53 V = 1


Garuti’s Compatibility index


𝐺=∑min (𝑥𝑖 , 𝑦 𝑖 )max (𝑥 𝑖 , 𝑦 𝑖 )

(𝑥 𝑖+𝑦 𝑖 )/2

Three compatible vectorsi xi yi zi

1 .450 .490 .499

2 .300 .300 .300

3 .200 .200 .200

4 .050 .010 .001

G = .93 G = .98

http://www.amazon.com/Group-Decision-Making-Reconciling-Differences/dp/1888603089/ref=ntt_at_ep_dpi_3


Supply Chain Management

1. Supplier selection of blanking dies2. Distribution center location3. Selection of third-party logistic provider


https://core.expertchoice.com/


Supplier selection of blanking dies




Normal Ideal Distribute

Supplier 4 18.15% 100% 25.93%

Supplier 3 17.53% 96.64% 25.06%

Supplier 1 17.32% 95.43% 24.75%

Supplier 2 16.98% 93.55% 24.26%

Supplier 5 15.17% 83.58%

Supplier 6 14.84% 81.76%




Distribution center location




Origin Central-West North Northeast South Southeast

Sao Paulo 7 17 12 4 5

Parana 8 18 13 3 6

Santa Catarina 8 18 13 3 6

Rio Grande do Sul 9 19 14 3 7

Delivery time in days




Origin Ideal Normal

Sao Paulo 100.00% 55.61%

Parana 35.33% 19.65%

Santa Catarina 35.33% 19.65%

Rio Grande do Sul 9.16% 5.09%

Results with AHP application




Origin Ideal (ANP) Normal (ANP) Normal (AHP)

Sao Paulo 100.00% 39.00% 55.61%

Parana 70.33% 27.73% 19.65%

Santa Catarina 70.33% 27.73% 19.65%

Rio Grande do Sul 13.00% 5.12% 5.09%

Results with AHP application

G = .72S = 1.08



Selection of third-party logistic provider



Selection of third-party logistic provider

Level Performance

Excellent 1.00From excellent to very good 0.75

Very good 0.49

From very good to good 0.25

Good 0.10

Poor 0.06

Supplier B O C R PV1 PV2

1 35% 43% 20% 28% 33.2 % 36.1 %2 35% 27% 21% 38% 33.8 % 32.7%

3 30% 30% 39% 34% 33.0 % 31.2% G = .94

Innovative and practical issues of multi-criteria decision-making in the supply chain management

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