Uncertain Supply Chain Management A P-robust model in humanitarian logistics in a non-neutral political environment

Humanitarian assistance by foreign organizations in general and foreign military forces in particular, is typically provided in a non-neutral political environment. Local politics that range from national pride, through strained relations with the country offering military logistic support, to blatant aversion to the population in need, affect the ability to provide effective humanitarian aid. The current paper presents the use of mathematical modeling and robustness approach when the government of the affected area declines offers of aid from international organizations because of political constraints. The multi-objective model seeks to minimize unsatisfied demands and total costs of the government and suppliers. To explore the effects of various parameters and show managerial insights that can guide DMs under a variety of conditions, the sensitivity analysis of the experiments are presented

A robust optimization model for logistics planning in the earthquake response phase

In this paper, a robust bi-level model is proposed to optimize decisions related to distribution and evacuation aid after earthquake. Usually in disastrous situation foreign countries help the affected country by sending relief commodities. In this problem, the foreign countries try to minimize their shipping costs and the affected country seeks to minimize its total costs which include inventory, operation, and transportation expenses. This situation is a game between different decision makers after a catastrophic disaster. To deal with this situation, a bi-level model is proposed in which the affected country is the leader and suppliers are the followers. To validate the proposed robust model, we consider Tehran probable earthquake in region 1 as a case study. Then the advantages of using bi-level modeling against considering just one player's point of view is provided. The sensitivity analysis of the experiments are presented to explore the effects of various parameters to show managerial insights that can guide DMs under a variety of conditions