Multi-stage multi-product multi-period production planning with sequence-dependent setups in closed-loop supply chain

Abstract

A multi-stage lot sizing problem with remanufacturing is modelled.Sequence dependent setups and setup carry-over in a flow shop are considered.A mixed integer programming is introduced to formulate the problem.Rolling horizon heuristics and a SA algorithm are proposed to solve the model.For large size problems SA algorithm would have better solutions than heuristics. This paper studies multi-stage multi-product multi-period capacitated production planning problem with sequence dependent setups in closed-loop supply chain. In this problem, manufacturing and remanufacturing of each product is regarded consequently, and in addition to the setup for changing products, a setup while changing the processes is needed. To formulate the problem, a mixed-integer programming (MIP) model is presented. Four MIP-based heuristic named non-permutation and permutation heuristics, using rolling horizon are utilized to solve this model. Moreover, a simulated annealing algorithm using a heuristic to provide initial solution is developed to solve the problem. To calibrate the parameters of the proposed simulated annealing algorithm, Taguchi method is applied. The numerical results indicate the efficiency of the proposed meta-heuristic algorithm against MIP-based heuristic algorithms.