Multi-Objective Mathematical Model for Location, Allocation and Distribution of Relief Commodities under Uncertainty

In this paper, decisions about different phases of crisis management cycle are modeled in the form of an integrated mathematical programming model based on the assumption of the real situation of the crisis. Goals are minimizing the number of injured people who are not serviced and minimizing the cost of relief supplies in affected areas. Simultaneous optimization of locating problems of relief bases, allocation of resources, distribution and delivery of relief supplies and evacuation of injured (pre and post-crisis situations) are among the innovations of this research. Therefore, scenarios based on existing faults (four faults) in region one of city of Tehran are considered. In this study, first, we present a binary integer programming model. To validate the model, the Epsilon Constraint method in software environment of GAMS with the CPLEX solver has been used to solve the problem in small scale. To solve the problem in large scale, we have investigated a case study using the data of relief bases in region one of Tehran city. The case study was also investigated using non-dominant sorting Genetic approach. The results of the research show that the non-dominant sorting Genetic approach can solve the model with the least error than the exact solution and in less time.