Genetic Algorithm for Solving Location Problem in a Supply Chain Network with Inbound and Outbound Product Flows

This paper considers a location problem in a supply chain network. The problem addressed in this paper is motivated by an initiative to develop an efficient supply chain network for supporting the agricultural activities. The supply chain network consists of regions, warehouses, distribution centers, plants, and markets. The products include a set of inbound products and a set of outbound products. In this paper, definitions of the inbound and outbound products are seen from the region’s point of view. The inbound product is the product demanded by regions and produced by plants which flows on a sequence of the following entities: plants, distribution centers, warehouses, and regions. The outbound product is the product demanded by markets and produced by regions and it flows on a sequence of the following entities: regions, warehouses, and markets. The problem deals with determining locations of the warehouses and the distribution centers to be opened and shipment quantities associated with all links on the network that minimizes the total cost. The problem can be considered as a strategic supply chain network problem. A solution approach based on genetic algorithm (GA) is proposed. The proposed GA is examined using hypothetical instances and its results are compared to the solution obtained by solving the mixed integer linear programming (MILP) model. The comparison shows that there is a small gap (0.23%, on average) between the proposed GA and MILP model in terms of the total cost. The proposed GA consistently provides solutions with least total cost. In terms of total cost, based on the experiment, it is demonstrated that coefficients of variation are closed to 0