Capacitated Dynamic Lot-sizing for Remanufacturing Systems: Mathematical Model and Solution Algorithm

Abstract

This thesis considers a dynamic lot-sizing problem in remanufacturing systems. Remanufacturing, one of product recovery options, is an emerging industry in which end-of-life products are reprocessed in such a way that their appearances and qualities are as good as new. In this study, we consider the system configuration with a single disassembly, parallel reprocessing and a single reassembly facilities, and the problem is to determine the disassembly, reprocessing and reassembly lot-sizes while satisfying the demands of remanufactured product over a given planning horizon. As an extension of the previous study, we consider the capacity constraints explicitly, and hence more realistic solutions can be provided for operating remanufacturing systems. To represent the problem mathematically, a mixed integer programming model is developed for the objective of minimizing the sum of setup, operation and inventory holding costs. Then, due to the complexity of the problem, we suggest fix-and-optimize heuristics in which the solutions are obtained by fixing a portion of binary variables and solving the resulting mixed integer programming models iteratively. Computational experiments were done on various test instances and the results show that the heuristics give near optimal solutions.