An integrated model for supplier location-selection & order allocation under capacity constraints in an uncertain environment

Facility/supplier location-allocation and supplier selection-order allocation are two of the most important decisions for both designing and operation supply chains. Conventionally these two issues will be discussed separately. Due to similarity and relationship between these issues, in this paper we investigate an integrated model for supplier location-selection and order allocation problem in supply chain management (SCM). The objective function is set in such a way that the establishment costs, inventory-related costs, and transportation costs as quantitative criteria have been minimized. As regards, the costs are uncertainty, therefore we have considered them stochastic. This paper developed a bi-objective model for optimization of the mean and variance of costs. Also, the capacities of supplier are limited. This mixed integer nonlinear program solved with two meta-heuristics genetic algorithm and simulated annealing. Finally, these two methods compared in terms of both solution quality and computational time. To obtain a high degree of validity and reliability GAMS software and meta-heuristic results in small sizes compared.