A memetic algorithm with extended random path encoding for a closed-loop supply chain model with flexible delivery
First online: 07.11.2016
Cite this article as: Behmanesh, E. & Pannek, J. Logist. Res. (2016) 9: 22. doi:10.1007/s12159-016-0150-y
Logistics network design is a major strategic issue in supply chain management of both forward and reverse flow, which industrial players are forced but not equipped to handle. To avoid sub-optimal solution derived by separated design, we consider an integrated forward reverse logistics network design, which is enriched by using a complete delivery graph. We formulate the cyclic seven-stage logistics network problem as a NP hard mixed integer linear programming model. To find the near optimal solution, we apply a memetic algorithm with a neighborhood search mechanism and a novel chromosome representation including two segments. The power of extended random path-based direct encoding method is shown by a comparison to commercial package in terms of both quality of solution and computational time. We show that the proposed algorithm is able to efficiently find a good solution for the flexible integrated logistics network.
Memetic algorithm Closed-loop supply design Random path Flexible delivery