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.
This paper investigates credit allocation policy making and its effect on economic development using bi-level programming. There are two challenging problems in bi-level credit allocation; at the first level government/public related institutes must allocate the credit strategically concerning sustainable development to regions and industrial sectors. At the second level, there are agent banks, which should allocate the credit tactically to individual applicants based on their own profitability and risk using their credit scoring models. There is a conflict of interest between these two stakeholders but the cooperation is inevitable. In this paper, a new bi-level programming formulation of the leader-follower game in association with sustainable development theory in the first level and data mining classifier at the second level is used to mathematically model the problem. The model is applied to a national development fund (NDF) as a government related organization and one of its agent banks. A new algorithm called Bi-level Genetic fuzzy apriori Algorithm (BGFAA) is introduced to solve the bilateral model. Experimental results are presented and compared with a unilateral policy making scenario by the leader. Findings show that although the objective functions of the leader are worse in the bilateral scenario but agent banks collaboration is attracted and guaranteed.