Abstract

We study a static and dynamic disassembly assembly routing problem with returns (2D-ARP-R). The problem presents the case where a set of disassembled components and raw materials are converted into a final product. By regrouping production and routing decisions, it is possible to synchronise different activities (assembly, disassembly, inventory management, and vehicle routing) and build a global optimal solution. A mixed integer linear programming (MILP) is presented to solve this new variant. A mat-heuristic based on integer programming and variable neighborhood search algorithm (VNS) is also developed to solve the larger size instances. Numerical results show that the mat-heuristic approach improves the upper bounds obtained by CPLEX in a much shorter time, in most cases. We also evaluate the benefits of coordination of the production and routing decisions within the same optimisation model. This benefit can reach up to 117.38% compared to the hierarchical approach. [Submitted: 4 April 2020; Accepted: 27 June 2021]

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