Solution approaches for improving performances and logistics network structures of humanitarian relief organizations under uncertainty

The main objective of the HRL is to acquire and deliver the requested supplies and services, at the places and times they are needed, while ensuring best value for money. These critical supplies are vital in post disaster activities for survival, such as food, water, temporary shelter and medicine, among others. It directly focuses on helping the sufferers and injured people on disaster areas. Efficient and effective preparedness and response planning can significantly decrease the social, economic and environmental impacts of disasters. Hence, operations research and management science perspectives and techniques for HRL are very suitable and they can play a great role for preparing the society and reducing the negative impacts of disasters. In humanitarian relief logistics literature, NGOs play a significant role in relief activities by the reasons of insufficient resources and funding of governmental relief organizations. Hence, the efficient and effective preparedness and response abilities of the NGOs are crucial to obtain efficient relief activities and its performances must be improved. Therefore, it is very important for NGOs to apply an appropriate approach to evaluate their preparedness and response abilities. In this study, different multi criteria decision making approaches based on interval type-2 fuzzy sets are proposed to evaluate emergency preparedness and response ability performances of NGOs. The proposed hybrid approach is applied for NGOs in Turkey to evaluate their performances. The importance weights of the critical success factors are determined using AHP based on interval type-2 fuzzy sets. Then, TOPSIS, PROMETHEE, and ELECTRE based on interval type-2 fuzzy sets are applied to evaluate preparedness and response abilities of NGOs. The obtained results are compared with each other and some suggestions are presented to humanitarian relief organizations to improve their humanitarian relief performances. There are limited numbers of studies for corporations the activities of both NGOs and governmental humanitarian relief organizations and optimizing it. Another contribution of this thesis is to propose a two-stage stochastic programming model using both NGOs' and governmental humanitarian relief organizations' resources together under demand uncertainty. In this model, total cost of fixed opening, transportation, and penalty of unmet demand are considered. A sample average approximation algorithm is also proposed to solve the problem and evaluate the results of two-stage stochastic programming model. We validate the mathematical model by generating a base case scenario using real data for possible earthquake of Istanbul. Also, a sensitivity analysis is performed on the parameters of the proposed mathematical model and SAA algorithm, and the findings are discussed.