Abstract:
Humanitarian logistics management has become a very important issue now a
day due to increase in different types of disasters in recent years all around the
world. When disaster strikes proper management of relief network is essential
as any indulgence might be met with severe penalty like loss of valuable human
lives. Another important issue is the uncertain nature of disasters as we don’t
know where disaster will occur or at what magnitude. In case of a disastrous
event, decision making usually involves selection of proper locations for aid
distribution centers, distribution of relief goods to different demand nodes,
proper vehicle management for transportation of relief goods etc. In this thesis
a multi echelon multi objective logistics model will be developed which will
attempt to find optimal locations for setting up regional relief distribution
centers with minimum setup cost and then it will find the optimal quantity of
goods flow among different nodes and stages of the relief supply chain to
minimize the relevant distribution cost and while doing that will minimize both
the unmet demand and amount of unitized relief goods in presence of demand
and supply uncertainty. Hence the model under consideration spans from
opening of local distribution facilities, to initial allocation of supplies, to last
mile distribution of aid, i.e. all three echelons of humanitarian logistics
network. The model will also seek to optimize the number trips that are needed
to be made by different types of vehicles for efficient distribution of relief
goods among different nodes of the network. At the end a case study will be
incorporated in which an example problem of the model will be solved and
optimized using metahuristic algorithms to demonstrate the models
effectiveness. Two suitable algorithms: Firefly Algorithm (FA) and Bat
Algorithm (BA) have been used for this purpose. Results obtained from both
algorithms shows Pareto optimality, but Bat Algorithm seemed to be capable of
solving the model in shorter period of time than Firefly Algorithm for the same
number of iterations.
