A Metaheuristic Algorithm for a Bi-objective Supply Chain Design Problem

Abstract: A supply chain design problem based on a two-echelon single-product system is addressed. The product is distributed from plants to distribution centers and then to customers. There are several transportation channels available for each pair of facilities between echelons. These transportation channels introduce a cost-time tradeoff in the problem to formulate a bi-objective mixed-integer programming model. The decisions to be taken are the location of the distribution centers, the selection of the transportation channels and the flow between facilities. Since this problem is NP-hard a metaheuristic algorithm was developed to solve it. The metaheuristic algorithm is composed of three methods. The constructive method generates solutions using a random strategy for opening distribution centers and a weighted greedy function to select the transportation channel. The improvement method uses local search with a dominance strategy. The combination method is used for post-processing and is based on a Path Relinking scheme. The proposed algorithm was compared with a previously developed e-constraint based algorithm and over instances of different size. For the smallest instances, as expected, the reference algorithm was more efficient in terms of computing time and solution quality. However, for the largest instances with similar run times the metaheuristic algorithm achieved better results.