UNHCR Project Report
-
Upload
absar-ahmad -
Category
Documents
-
view
25 -
download
0
description
Transcript of UNHCR Project Report
UNHCR AID DISTRIBUTION
ABSAR AHMAD 2012020
FAIZAN ARIF 2012100
HAMZA BILAL 2012124
OMER ZAMAN 2012296
UNHCR AID DISTRIBUTION | 2
Executive Summary Supply Chain of Aid Distribution organizations are one of the most complex supply chains all over the
world. In this report, we will critically analyze the aid distribution of UNHCR based on various aid
distribution supply chain models. Three models are chosen to analyze the supply chain of UNHCR i.e
Humanitarian Relationship Model, Last Mile Aid Distribution Model and Transshipment Model. Each
model is explained and then compared with UNHCR to compare between ideal model and real time
applied model. The later ones mathematical models and are explained using hypothetical examples. In
the end, conclusion is drawn and some future recommendations to better the aid distribution of UNHCR
are discussed.
UNHCR AID DISTRIBUTION | 3
TABLE OF CONTENTS
Executive Summary 2
INTRODUCTION 4
THE HUMANITARIAN RELATIONSHIP MODEL 4
Relationship with Government 5
Relationship with Donor 5
Relationship with Military 5
Relationship with NGOs 5
Relationship with Logistic / Other Companies 5
Relationship with Aid Agencies 6
Last Mile Aid Distribution Model 6
Hypothetical Example 7
Model Formulation 7
Application in UNHCR 9
Transshipment Model 9
Objective Function 9
Constraints 10
Analysis 11
Recommendations 11
References 14
WORDCOUNT 15
Appendix 16
UNHCR AID DISTRIBUTION | 4
INTRODUCTION The Office of the United Nations High Commissioner for Refugees was established on December 14,
1950 by the United Nations General Assembly. The agency is mandated to lead and co-ordinate
international action to protect refugees and resolve refugee problems worldwide. Its primary purpose is
to safeguard the rights and well-being of refugees. It strives to ensure that everyone can exercise the
right to seek asylum and find safe refuge in another State, with the option to return home voluntarily,
integrate locally or to resettle in a third country. It also has a mandate to help stateless people
UNHCR’s priority in Pakistan is to achieve lasting solutions for one of the largest and most protracted
refugee situations in the world. Pakistan continues to host approximately 1.5 million refugees. Most are
from Afghanistan and live in refugee villages and urban areas. Since March 2002, UNHCR has
facilitated the return of approximately 3.9 million registered Afghans from Pakistan.
THE HUMANITARIAN RELATIONSHIP MODEL Humanitarian Relationship model engages very different players, who have a very high degree of
heterogeneity in terms of their interests and expertise. The key players are governments, military, aid
agencies, NGOs, Donors and Logistic Companies. The Government has the power to authorize
operations in case of an emergency. The military provides security in areas of emergency for the
organizations. The military and national aid agencies can start acting on their own without the call by the
government. Within the company category, logistics service providers are excellent contributors at each
stage of a disaster-relief operation
through their logistics and supply
chain management core
capabilities. Since each player
within its own specific role can
provide in-kind donations, in the
humanitarian relationship model
the term ‘‘donor’’ refers to those
who exclusively give financial
means to fund aid operations.
Comparing the structure of
UNHCR’s aid and supply with
the model, we find out that
UNHCR lies in the heart of the
model. In the model where everyone is directly connected to everyone, UNHCR lies in the center of it.
Making this modification, we implement this model on UNHCR.
UNHCR AID DISTRIBUTION | 5
Relationship with Government
UNHCR’s main governmental counterparts for ref
ugees in Pakistan are the Ministry of States and Fr
ontier Regions (SAFRON), the Chief Commission
erate for Afghan Refugees (CCAR) and the Com
missioneratesfor Afghan Refugees (CARs) in the
Provinces.In addition, UNHCR works with the Na
tional Database and Registration Authority (NAD
RA), the Ministry of Foreign Affairs, Ministry of I
nterior, the Economic Affairs Division (EAD) and
the Ministry of Interior.
Since 2002, UNHCR has facilitated the return of 3.8M refugees.
Relationship with Donor
Relationship with Military
UNHCR's humanitarian activities may be linked to the military in
two ways. First, where law and order are lacking and humanitarian
activities are carried out in an insecure environment, peacekeepers
or other international armed forces may be mandated by the Security
Council to ensure the secure delivery of assistance to the victims of
the conflict in question. Second, military resources may be used to
augment the capacity of UNHCR to implement the High
Commissioner's mandate.
Relationship with NGOs
Relationship with Logistic / Other Companies
The objective of UNHCR’s procurement policy is to provide
the beneficiaries with appropriate quality products or services
at the specified time and place and at the lowest total cost.
National NGOs
Tamer-e-Khalq Foundation
Taraqee Foundation – Pakistan
Frontier Primary Health Care –
Pakistan
Union Aid for Afghan Refugees –
Pakistan
Water, Environment and
Sanitation Society – Pakistan
Women Empowerment Organization
UNHCR is working with the National and International NGO
partners to distribute its items to the refugees and disaster
affected areas.
In 2014 it was working with 18 national and 08 international
NGO partners
International NGOs
Church World Service – USA Council for Community
Development Courage Development
Foundation Dost Welfare Foundation Drugs and Narcotics Educational
Services for Humanity
Contributions to UNHCR for the budget year 2015 (as at 18
September 2015) were $ 2,761,507,854 from over 120 sources
which include both countries and the private donors.
Top Goods Procured in 2014 based on
US Dollar
UNHCR Presence
UNHCR AID DISTRIBUTION | 6
UNHCR hires consultants and specialized companies and their staff for projects.
UNHCR does not purchase from companies engaged directly or indirectly engaged in sale or
manufacture of anti-personnel mines or any similar operations. It also does not engage with companies
who do not follow the practices consistent with the rights set for th in the Convention on the Rights of
the Child.
UNHCR’s Department of Emergency, Security and Supply (DESS) comprises the Procurement Service
(PS), and the Supply Management and Logistics Service (SMLS). These are responsible for global
supply chain management, operational support, planning and reporting on the use of resources.
Relationship with Aid Agencies
In Badin and Thatta, UNHCR has been
working with the National Rural Support
Programme, a Pakistani aid group, which is
delivering the items and establishing small
tent villages of less than 100 families. The
scarcity of dry land on which to pitch the
tents remains a challenge.
Last Mile Aid Distribution Model
Last Mile Aid Distribution
deals with the final stage of
a humanitarian relief chain.
It is concerned with the
delivery of relief supplies to
the calamity affected people
from a local distribution
hub. Local distribution
center or hub is a small
facility situated near
calamity affected area and
holds some inventory of
relief supplies. When the
disaster occurs, LDC
distributes emergency relief
Procurement in UNHCR
UNHCR AID DISTRIBUTION | 7
supplies to its corresponding demand locations.
The journal gives us two-phase modeling approach to determine a delivery schedule for each vehicle
and make inventory allocation decisions by considering supply, vehicle capacity, and delivery time
restrictions. Logistical problems in the last mile starts from the limitations related to transportation
resources and emergency supplies, difficulties due to damaged transportation infrastructure, and lack of
coordination among relief actors. Last Mile Distribution Model is a mathematical model which takes
certain input data values (i.e vehicle capacity, vehicle type etc.) and quantitatively analyzes three main
operational decisions. These main decisions are
Amount of supplies to be provided at demand location
Determining the number and type of vehicle to be used
Determining the delivery routes for each vehicle
Last mile distribution model minimizes the transportation cost and unsatisfied or late satisfied customers
keeping in mind time and inventory constraints.
Hypothetical Example
In order to understand this model, let’s take a hypothetical example. First of all, the list of required
variables is listed as follows
Model Formulation
Now, we will consider a
simple one LDC and two node
problem. Let us consider a
disaster has occurred and there
are 2000 affected families at
node 1 and 1000 at node 2.
LDC has two mini trucks with
capacity of 500 units and two
large trucks with capacity of
1000 units. The present
inventory at LDC is 3500 units.
Cost for mini truck from LDC to node 1 is 1000 Rs. and for large truck is 2000 Rs. Similarly, Cost for
mini truck from LDC to node 2 is 1500 Rs. and for large truck is 2500 Rs. It is assumed that it is a one
day problem and 1 family requires 1 unit to satisfy its demands.
Variable Description
K Set of Vehicles
R Set of Routes
N Set of all demand locations
N Set of demand locations visited on route r ∈ R
Crk Cost of route r for vehicle k ∈ K
Qk Capacity of vehicle k ∈ K (volume)
Trk Duration (as a fraction of a day) of route r ∈ R for vehicle k ∈ K
dn Demand at n location
D Total Demand
I Inventory at LDC
UNHCR AID DISTRIBUTION | 8
Given data
K {1, 2}
R {1, 2}
N 2
C11 1000 rs
C12 2000 rs
C21 1500 rs
C22 2500 rs
Q1 500 units
Q2 1000 units
d1 2000 units
d2 1000 units
D 3000 units
I 3500 units
Now, first we will check our inventory constraint
I >= D
3500 >= 3000
So, our inventory constraint is satisfied.
Now, we will check demand constraint
∑ 𝑄𝑘 ≥ 𝑑𝑛
Since, d1 is 2000 and d2 is 1000 units so we can only have two conditions in which this constraint will be
satisfied.
1ST CONDITION: Two Large trucks go to node 1 and two mini trucks go to node 2.
2ND CONDITION: Two mini trucks & one large truck go to node 1 and one large truck go to node 2.
Now, we will calculate cost for each condition
minimize (Total Cost) = ∑ 𝐶𝑟𝑘
For 1st Condition
Total Cost = 2000 + 2000+ 1500 + 1500
Total Cost = 7000 Rs.
UNHCR AID DISTRIBUTION | 9
For 2nd Condition
Total Cost = 2000 + 1000+ 1000 + 2500
Total Cost = 6500 Rs.
Since, total cost should be minimized, so we will select 2nd condition to transfer our supplies to the
affected area.
This is how Last mile Aid Distribution Model give us no. of vehicles and route schedules and optimizes
our cost. This was a very simple example. Real life examples are much more complex and require more
input data to optimize solution.
Application in UNHCR
UNHCR does not apply Last Mile Aid Distribution Model in mathematical form rather they apply it
based on their experience. They have contract with local transportation companies that deliver them
transport whenever the need arises. The local drivers are aware of every route and they know the
transportation cost for each route and they select the route with minimum cost. So, UNHCR does not
imply with Last Mile Distribution in mathematical form rather it relies on the experience of its drivers.
Transshipment Model Transshipment model is a mathematical model which is usually used by business organizations for
minimizing the cost of transportations and making an efficient supply chain. Using a transshipment
model in aid distribution process could make the supply chain very cost effective and efficient. In this
mathematical model basically we define an objective function which defines the vision of aid
distribution.
Objective Function
So the objective function of this model is to meet unsatisfied demand accumulated over time. However,
cost cannot be completely ignored and so needs to be minimized and included in the objective function.
The “Humanitarian Organizations Code of Conduct” requires that aid must be delivered based on need
and not cost (Sphere Project, 2004; IRFC, 1994b).
UNHCR AID DISTRIBUTION | 10
Minimize
𝑤 ∑ 𝑈𝑘𝑖𝑡
𝑘𝑖𝑡
+ 𝑥 ∑ 𝐹𝑘𝑗𝑣
𝑘𝑗𝑣𝑡
𝑉𝑘𝑗𝑣𝑡 + 𝑦 ∑ 𝐼𝑘𝑖𝑡
𝑘𝑖𝑡
+ 𝑧 ∑ 𝑉𝑘𝑗𝑣𝑡 ………………………………………..(1)
𝑘𝑗𝑣𝑡
1
Variable w,x,y,z are basically weights that are defined by organization. For Example, if we put w=1,
x=0.001, y=0.01, z=1 in eq(1) we get
1 ∑ 𝑈𝑘𝑖𝑡
𝑘𝑖𝑡
+ 0.001 ∑ 𝐹𝑘𝑗𝑣
𝑘𝑗𝑣𝑡
𝑉𝑘𝑗𝑣𝑡 + 0.01 ∑ 𝐼𝑘𝑖𝑡
𝑘𝑖𝑡
+ 1 ∑ 𝑉𝑘𝑗𝑣𝑡 ………………………………………..(1∗)
𝑘𝑗𝑣𝑡
this means that new objective function (1*) places much greater priority on minimizing need before
transportation and inventory costs.
The weight values of 1, 0.001, 0.01 and 1 in expression are somewhat arbitrary, and here simply reflect
the relative magnitude each particular component in the policy of the organization. We wished the items
to be delivered to recipients as quickly as possible, hence the high relative weighting given to Pkit Ukit.
The units of measurement of each component must also be taken into account. At first glance it may
appear that there is a greater weighting given to inventory than transport. However, the magnitude of the
transportation costs means that its weighting has to be scaled down in order for transportation costs to
approximately equal inventory costs. The danger with using weightings is that if there was a small
transportation cost and a large inventory then these weightings may be inappropriate leading to the
inventory component having a greater influence than the transportation costs weighting. The weightings
have been verified so that this problem should not occur.
Constraints
To establish initial conditions, constraint (A) and (B) specifies the current unsatisfied demand and
inventory of each item at each node, i.e., at the end of day 0:
𝑈𝑘𝑖0 = 𝑈𝑘𝑖0 … … . … . . (𝐴)
𝐼𝑘𝑖0 = 𝐼𝑘𝑖0 … … . … . . (𝐵)
Each time the model is re-run during the course of the relief operation, the values of parameters Uki0 and
Iki0 would be updated to reflect the situation at the time of planning.
𝑇𝑗𝑘𝑣𝑖𝑡 = 𝑇𝑗𝑘𝑣𝑖𝑡0 … … . … . . (𝐶)
Constraint (C) defines the amount of each item sent between pairs of nodes before the disaster has
occurred but which are still in transit and so have not yet arrived at the destination node.
1 all the variables & indices are defined and described in nomenclature.
UNHCR AID DISTRIBUTION | 11
∑ 𝑇𝑗𝑘𝑣𝑖𝑡 − 𝐿𝑗𝑘𝑣
𝑗𝑣
+ 𝐼𝑘𝑖,𝑡−1 + 𝑈𝑘𝑖,𝑡−1 = ∑ 𝑇𝑗𝑘𝑣𝑖𝑡 + 𝐼𝑘𝑖𝑡
𝑗𝑣
− 𝑈𝑘𝑖𝑡 + 𝐷𝑘𝑖𝑡 … … . … . . (𝐷)
Constraint (D) ensures that no more items are sent than are received and/or taken from the local
inventory. Constraint (D) states that, on any given day and at any given node, the items arriving from
previous nodes, together with the items inherited from the previous day’s ending inventory, less the
unmet demand from the previous day, should equal in quantity the items sent to the next nodes, plus the
demand and the amount put into inventory, less any unsatisfied demand.
𝑉𝑘𝑗𝑣𝑡 ≥0.001 ∑ 𝑇𝑘𝑗𝑣𝑖𝑡𝑊𝑖𝑖
𝑉𝐶𝑣… … . … . . (𝐸)
Constraint (E) ensures that there are enough vehicles to transport items between nodes. The coefficient
0.001 converts the item weights in kilograms to metric tons, the units of vehicle capacity.
0.001 ∑ 𝐼𝑘𝑖𝑡𝑊𝑖 ≤ 𝐶𝑘
𝑖
… … . … . . (𝐹)
Constraint (F) ensures that the weight of all inventory items is within the node capacity limits, again
multiplying by 0.001 to convert from kilograms to metric tons.
Thus our objective function (1) should be minimized under constraints (A-F).
Analysis
After applying these models, it is analyzed that UNHCR is following all three models. Since UNHCR
has direct relations with government of Pakistan, Humanitarian Relationship model is being fully
implemented as military and other aid agencies too have relationship with UNHCR. The two
mathematical models described are not implemented in mathematical form rather they are applied based
on the experience of the drivers.
Recommendations As described in the report, UNHCR does not follow any mathematical model. It distributes its supplies
with the transportation companies and transportation cost is minimized by qualitative analysis of drivers.
The efficiency of aid distribution can be increased significantly if UNHCR apply any mathematical
model. Data should be gathered for all the routes and available vehicles. Excel sheets should be
generated to optimize transportation cost in any given condition. This will be very helpful and efficient
for UNHCR if they are able to apply it.
UNHCR AID DISTRIBUTION | 12
Journal Article 2 Summary
Title & reference “Humanitarian Logistics and Supply Chain Management” A. Cozzolino, Humanitarian
Logistics
Topic Humanitarian Relationship Model
Main Argument Determining the relationship between different organizations working in a very different
aspects in a disaster / refugee affected area
Finding & most
interesting point
The close relationship between governments, organizations, military and different aid
agencies work in close proximity towards providing aid to refugees and disaster affected
areas
Methodology Qualitative: The level of relationship between different players determine an efficient
distribution of necessary aid to the Individuals
Implications This model is implied such that each players works together to achieve a better future of the
people affected
Relation to our
report
Our report focusses on relation of UNHCR with various different players, it works with to
provide better aid and facilities to the Refugees
Journal Article 1 Summary
Title &
reference
“A transshipment model for distribution and inventory relocation under
uncertainty in humanitarian operations” in “Socio-Economic Planning Sciences” Journal
by Beate Rottkemper and others.
Topic A mathematical model for managing a disaster
Main Argument Unsatisfied need should be satisfied first irrespective of cost or any other factor.
Finding & most
interesting point
It is interesting that a mathematical model that is normally used in business could also be
used for aid distribution.
Methodology Qualitative and Quantitative based on secondary data
Implications Applied on a real time scenario
Relation to our
report
We have used this model to minimize the cost for a continuous running aid programe.
UNHCR AID DISTRIBUTION | 13
Journal Article 3 Summary
Title & reference Last Mile Distribution in Humanitarian Relief
Journal of Intelligent Transportation Systems, 12(2):51–63, 2008
Topic Last Mile Distribution in Humanitarian Relief
Main Argument The main objective of this journal is to minimize the sum of transportation
Finding & most
interesting point
It is interesting to note that transportation system of aid organizations can also be made
highly cost efficient.
Methodology A quantitative two-phase modeling approach to determine a delivery schedule for each
vehicle and make inventory allocation decisions by considering supply, vehicle capacity,
and delivery time restrictions.
Implications It is applied in UNHCR on experience basis not in mathematical form
Relation to our
report
We critically analyzed aid distribution of UNHCR based on Last Mile Distribution Model
UNHCR AID DISTRIBUTION | 14
References
ReliefWeb, (2015). UNHCR Global Appeal 2015 Update - Pakistan. [online] Available at:
http://reliefweb.int/report/pakistan/unhcr-global-appeal-2015-update-pakistan [Accessed 1 Oct. 2015].
Unhcr.org, (2015). UNHCR - Pakistan. [online] Available at:
http://www.unhcr.org/pages/49e487016.html [Accessed 1 Oct. 2015].
Wassenhove, V. (2012). Humanitarian Logistics and Supply Chain Management. 1st ed. [ebook] p.page
no,13. Available at:
http://www.springer.com/cda/content/document/cda_downloaddocument/9783642301858-
c2.pdf?SGWID=0-0-45-1340522-p174501768. [Accessed 1 Oct. 2015].
Rottkemper, B., Fischer, K. and Blecken, A. (2012). A transshipment model for distribution and
inventory relocation under uncertainty in humanitarian operations. Socio-Economic Planning Sciences,
46(1), pp.98-109.
Clark, A. and Culkin, B. (2013). A Network Transshipment Model for Planning Humanitarian Relief
Operations After a Natural Disaster. Decision Aid Models for Disaster Management and Emergencies,
pp.233-257.
Refugees, U. (2015). Contributions to UNHCR for Budget Year 2015, as at 18 September 2015. [online]
UNHCR. Available at: http://www.unhcr.org/558a639f9.html [Accessed 3 Dec. 2015].
Refugees, U. (2015). Doing Business with UNHCR (2015). [online] UNHCR. Available at:
http://www.unhcr.org/3b9203194.html [Accessed 1 Dec. 2015].
Refugees, U. (2015). Introduction to UNHCR Procurement, 2015. [online] UNHCR. Available at:
http://www.unhcr.org/54aeb4f39.html [Accessed 5 Dec. 2015].
Refugees, U. (2015). Pakistan Fact Sheet. [online] UNHCR. Available at:
http://www.unhcr.org/5000210e9.html [Accessed 1 Dec. 2015].
Refugees, U. (2015). UNHCR Global Report 2005 - Working with partners. [online] UNHCR. Available
at: http://www.unhcr.org/449267810.html [Accessed 1 Dec. 2015].
Refugees, U. (2015). UNHCR Global Report 2014 - Working in partnership. [online] UNHCR.
Available at: http://www.unhcr.org/5575a78a0.html [Accessed 5 Dec. 2015].
Refugees, U. (2015). UNHCR Handbook for Emergencies, Third Edition (complete publication).
[online] UNHCR. Available at: http://www.unhcr.org/472af2972.html [Accessed 1 Dec. 2015].
UNHCR AID DISTRIBUTION | 15
Sciencedirect.com, (2015). A transshipment model for distribution and inventory relocation under
uncertainty in humanitarian operations. [online] Available at:
http://www.sciencedirect.com/science/article/pii/S0038012111000474 [Accessed 5 Dec. 2015].
Anon, (2015). [online] Available at: http://www.unhcr.org/publ/PUBL/3d5123714.pdf [Accessed 2 Dec.
2015].
Anon, (2015). [online] Available at: http://www.unhcr.org/4c08f2cb9.pdf [Accessed 5 Dec. 2015].
Anon, (2015). [online] Available at: http://www.unhcr.org/42ad4db40.pdf [Accessed 5 Dec. 2015].
Anon, (2015). [online] Available at: http://www.unhcr.org/48490bc52.pdf [Accessed 5 Dec. 2015].
Anon, (2015). [online] Available at:
http://www.fsa.ulaval.ca/personnel/renaudj/pdf/Recherche/2013/Chap1.pdf [Accessed 5 Dec. 2015].
Anon, (2015). [online] Available at: http://unhcrpk.org/wp-content/.../12/UNHCR-Pak-Fact-Sheet-June-
2014.pdf [Accessed 3 Dec. 2015].
Anon, (2015). [online] Available at: http://www.cbrewster.com/papers/Roy_ICMR12.pdf [Accessed 1
Dec. 2015].
Anon, (2015). [online] Available at: http://www.optimization-online.org/DB_FILE/2015/06/4963.pdf
[Accessed 1 Dec. 2015].
Word Count= 2307
UNHCR AID DISTRIBUTION | 16
APPENDIX
Humanitarian Relationship Model ................................................................................................ 17
TRANSSHIPMENT MODEL ...................................................................................................... 18
Abstract: .......................................................................................................................................................... 18
Last Mile Distribution in Humanitarian Relief ............................................................................. 21
SUMMARY ....................................................................................................................................................... 21
Mathematical Modeling ................................................................................................................ 22
Sets .................................................................................................................................................................. 22
Routing parameters ......................................................................................................................................... 22
Demand parameters ........................................................................................................................................ 23
Routing decision variables ................................................................................................................................ 23
Delivery decision variables ............................................................................................................................... 23
UNHCR AID DISTRIBUTION | 17
Humanitarian Relationship Model
Humanitarian relief-operation management engages very different players, who may have a high degree
of heterogeneity in terms of culture, purposes, interests, mandates, capacity, and logistics expertise. Key
players can be categorized as follow: governments, the military, aid agencies, donors, non-governmental
organizations (NGOs), and private sector companies—among which logistics service providers are
preeminent Governments—host governments, neighboring country governments, and other country
governments within the international community—are the activators of humanitarian logistics stream
after a disaster strikes since they
have the power to authorize
operations and mobilize
resources. In fact, without the
host government authorization,
no other player—with the
exception of national aid
agencies and the military—can
operate in the disaster theater.
On many occasions, the military
has been a very important actor
since soldiers are called upon to
provide primary assistance (i.e.,
hospital and camp installation,
telecommunications, and route
repair) thanks to their high
planning and logistic
capabilities.
Aid agencies are actors through
which governments are able to
alleviate the suffering caused by disasters. The largest agencies are global actors, but there are also many
small regional and country-specific aid agencies. Since each player within its own specific role can
provide in-kind donations, in the humanitarian relationship model the term ‘‘donor’’ refers to those who
exclusively give financial means to fund aid operations. Thus, in addition to country-specific funding
provided by governments in recent years, foundations, individual donors, and companies have become
important sources of funds for aid agencies.
Companies are capable of providing technological support and logistics staff and managers. They also
provide specific services that may no longer be available on the ground immediately after a disaster has
occurred, such as electricity supply, engineering solutions, banking support, and postal services.
Initially, companies are moved to participate in humanitarian efforts because they have observed that
enormous losses are inflicted when disasters interrupt the flow of their business; so they invest in re-
UNHCR AID DISTRIBUTION | 18
establishing their business continuity. Working to alleviate the economic impact of such disruptions
‘‘makes good business sense’’.
Within the company category, logistics service providers are excellent contributors at each stage of a
disaster-relief operation through their logistics and supply chain management core capabilities. Leading
international logistics service providers, such as Agility, DHL, FedEx, Maersk, TNT, and UPS, have
raised their importance in terms of the resources, assets, and knowledge shared with their humanitarian
counterparts.
TRANSSHIPMENT MODEL
Abstract:
The number of disasters and humanitarian crises which trigger humanitarian operations is ever-
expanding. Unforeseen incidents frequently occur in the aftermath of a disaster, when humanitarian
organizations are already in action. These incidents can lead to sudden changes in demand. As fast
delivery of relief items to the affected regions is crucial, the obvious reaction would be to deliver them
from neighboring regions. Yet, this may incur future shortages in those regions as well. Hence, an
integrated relocation and distribution planning approach is required, considering current demand and
possible future developments.
For this situation, a mixed-integer programming model is developed containing two objectives:
minimization of unsatisfied demand and minimization of operational costs. The model is solved by a
rolling horizon solution method. To model uncertainty, demand is split into certain demand which is
known, and uncertain demand which occurs with a specific probability. Periodically increasing penalty
costs are introduced for the unsatisfied certain and uncertain demand. A sensitivity analysis of the
penalty costs for unsatisfied uncertain demand is accomplished to study the trade-off between demand
satisfaction and logistical costs. The results for an example case show that unsatisfied demand can be
significantly reduced, while operational costs increased only slightly.
UNHCR AID DISTRIBUTION | 19
UNHCR AID DISTRIBUTION | 20
Nomenclature for Transshipment model
Sr No
Indices Description
1. t The index t represents a day within the planning horizon. Thus t = 1, ..., 10 means a
ten-day horizon. t = 1 means current day. t = 0 means day before today & t = -1 the day before that.
2. i The index i represent items transported.
3. v v denotes the type of vehicle.
4. j,k The indices j and k represents the network nodes in the supply chain such as
suppliers, airports, seaports, terminals, warehouses, and recipients etc.
Sr No
Variables Description
1. Capt available capacity time in each period t.
2. Iki0 current initial inventory at node k of item i (i.e., at the end of day 0)
3. Dkit demand at node k for item i on day t
4. Uki0 current unsatisfied demand at node k for item i
5. V Cv maximum capacity that each vehicle v can carry in metric tonnes
6. VAkvt number of vehicles available at node k of a vehicle type v on day t (integer)
7. Lkjv lead time from node k to node j using a vehicle of type v
8. Tkjvit0 amount of item i already sent from node k to node j, using a vehicle of type v, i at
past times t =−Lkjv,...,0
UNHCR AID DISTRIBUTION | 21
9. Fkjv fixed transport cost to include driver, fuel, maintenance etc. of using each vehicle
type v between node k and node j
10. Wi weight of each item i
11. Ck capacity limits of each node k
12. Tkjvit amount of item i sent from node k to node j, using vehicle type v, on day t
13. Vkjvt number of vehicles of type v sent from node k to node j on day t (integer)
14. Ikit inventory at node k of item i at the end of day t
15. Ukit unsatisfied demand (backlog) at node k for item i at the end of day t
Last Mile Distribution in Humanitarian Relief SUMMARY
Last mile distribution is the final stage of the relief chain; it refers to delivery of relief supplies from LDCs to the
people in the affected areas. LDC maybe a tent, a prefabricated unit, or an existing facility.
The journal gives us two-phase modeling approach to determine a delivery schedule for each vehicle and make
inventory allocation decisions by considering supply, vehicle capacity, and delivery time restrictions. Logistical
problems in the last mile starts from the limitations related to transportation resources and emergency supplies,
difficulties due to damaged transportation infrastructure, and lack of coordination among relief actors. The main
operational decisions related to last mile distribution are relief supply allocation, vehicle delivery scheduling, and
vehicle routing. The problems that arise during disaster relief operations may differ depending on various factors,
such as the type, impact, and location of the disaster, and local conditions in the affected regions.
As resource allocation and vehicle routing decisions are closely interrelated, they should be jointly considered. In
this respect, the last mile distribution problem is a variant of the inventory routing problem (IRP).
The main objective of this journal is to minimize the sum of transportation costs and penalty costs for unsatisfied
and late-satisfied demand. The last mile distribution problem determines the best resource allocation among
potential aid recipients in disaster affected areas that minimize the cost of logistics operations, while maximizing
the benefits to aid recipients. More specifically, the last mile distribution problem determines
delivery schedules
vehicle routes
the amount of emergency supplies delivered to demand locations during disaster relief
operations.
UNHCR AID DISTRIBUTION | 22
The required set of items required may vary greatly by situation depending on factors such as the type and the
impact of the disaster, demographics, and social and economic conditions of the area. We can categorize our
demand as Type1- and Type 2-based on their demand characteristics. Type 1 items are critical items for which
the demand occurs once at the beginning of the planning horizon It includes emergency supplies. Type 1
demands within a short period of time, due primarily to supply unavailability and vehicle capacity limitations. Once
Type 1 items arrive to the demand locations, they are immediately distributed to aid recipients. Therefore, we
assume that no Type 1 inventory is held at any demand location. Type 2 items are items that are consumed
regularly and whose demand occurs periodically over the planning horizon. Type 2 items are shipped to a
demand point, the excess amount can be held for consumption in future periods. We assume that any inventory
holding costs to store these items at the demand points is ignored, because it is likely negligible in relation to the
penalty costs associated with unsatisfied demand. The model serves an “equal allocation principle,” which
allocates supplies proportionally among the demand locations based on demand amounts and population
vulnerabilities, and balances the unsatisfied and late-satisfied demand among demand locations over time. The
relief system is likely unable to optimize the vehicle fleet, in terms of number, capacity, and compatibility after an
emergency. Hence, we assume that the vehicle fleet is comprised of a limited number of vehicles with different
characteristics. Each vehicle can be differentiated based on capacity, speed, and compatibility with various arcs in
the network. In practice, smaller trucks may be used to reach remote areas as roads may be poor or nonexistent,
while larger trucks may be used for areas that are closer and move easily reached. Demand parameters in our
model are based on the assessments done by relief agencies in the affected regions after the disaster
occurrence. The planning horizon parameter used in our model will be the worst case estimate. The length of the
planning horizon must be set to a length much longer than the expected relief horizon; the model will determine
when the delivery of relief supplies will be completed.
Mathematical Modeling
Following variables will be used in the model
Sets
T is set of days in the planning horizon; length of planning horizon.
K is set of vehicles.
R set of routes.
N set of all demand locations.
N set of demand locations visited on route r ∈ R.
E set of demand types: E = {1,2}.
Routing parameters
𝐶𝑟𝑘 is cost of route r for vehicle k ∈ K.
UNHCR AID DISTRIBUTION | 23
𝑞𝑘 capacity of vehicle k ∈ K (volume).
𝑇𝑟𝑘 duration (as a fraction of a day) of route r ∈ R for vehicle k ∈ K (from Phase 1).
Demand parameters
𝑑𝑖1 demand of type 1 at location i ∈ N (volume per planning horizon).
𝑑𝑖2 demand of type 2 at location i ∈ N on day t ∈ N (volume per day).
𝑝𝑖𝑡1 penalty cost factor for unsatisfied type 1 demand at location i ∈ N by day t ∈ T.
𝑝𝑖𝑡2 penalty cost factor for unsatisfied type 2 demand at location i ∈ N on day t ∈ T.
𝑎𝑡𝑒 amount of type e ∈ E relief supplies arriving to the LDC at the beginning of day t ∈ T.
Routing decision variables
𝑋𝑟𝑡𝑘= 1 if route r ∈ R is used by vehicle k ∈ K on day t ∈ T
0 otherwise.
Delivery decision variables
Yirtke amount of demand of type e ∈ E delivered to location i ∈ N on day t ∈ T by vehicle k ∈ K via
route r ∈ R
𝑊𝑖𝑒 penalty cost associated with unsatisfied type e ∈ E demand on day t ∈ T.
𝑆𝑖𝑡1 fraction of unsatisfied type 1 demand at location i ∈ N by day t ∈ T.
𝑆𝑖𝑡2 fraction of unsatisfied type 2 demand at location on day i ∈ N on day t ∈ T.
𝐼𝑖𝑡2 inventory level of type 2 at location i ∈ N at the beginning of day t ∈ T.
UNHCR AID DISTRIBUTION | 24
The basic function is given as:
UNHCR AID DISTRIBUTION | 25
The objective function (1a) minimizes the sum of routing costs and penalty costs for the backordered
Type 1 demand and for the lost Type 2 demand. Constraints (1b) determine the maximum penalty cost
for each day and for each item type. Constraints (1c) find the fraction of unsatisfied (backordered) Type
1 demand at a location over time while (1d) find the fraction of unsatisfied (lost) Type 2 demand at a
location on a day. Constraints (1e) guarantee that the entire Type 1 demand is satisfied by the end of the
planning horizon. Constraints (1f) ensure that the total amount of relief items of each type delivered to
all. Locations on a day is less than or equal to the amount of supplies available at the LDC. Constraints
(1g) and (1h) are vehicle capacity constraints and vehicle time constraints, respectively. Constraints (1i)
ensure that the fraction of unsatisfied demand is between zero and one. Constraints (1j) set the beginning
inventory level to zero at each location for Type 2 items. Constraints (1k) and (1l) are non-negativity
constraints, and (1m) define the binary routing variable.