Mathematical model and solution algorithms for capacitated dynamic lot-sizing in remanufacturing systems

Abstract

Remanufacturing is one of advanced product recovery options in which end-of-use/life products are reprocessed in such a way that their appearances and qualities are as good as new. In this study, we consider dynamic lot-sizing in remanufacturing systems that consist of a single disassembly facility, parallel reprocessing facilities and a single reassembly facility. The problem is to determine the disassembly, reprocessing and reassembly lot-sizes that satisfy the remanufactured product demands over a planning horizon. As a significant extension of the previous study, we consider the processing time capacity of each facility explicitly, and hence more realistic and applicable solutions can be obtained. 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 problem complexity, we suggest three variants of the fix-and-optimize based heuristic that fixes a portion of binary variables and solves the resulting problems iteratively. Computational experiments were done on various test instances and the test results show that the one that fixes the binary setup variables by the overlapped-period method performs better than the others and gives near optimal solutions within a reasonable amount of computation time.