Heuristics for integrated job assignment and scheduling in the multi-plant remanufacturing system

Abstract

We consider a multi-plant remanufacturing system where decisions have to be made on the choice of plant to perform the remanufacturing and the remanufacturing options. Each plant is in different geographical locations and differs in technological capability, labour cost, distance from customers, taxes and duties. There are three options of remanufacture: replacement, repair and recondition. Furthermore, the probability that each remanufacture job needs to be reworked depends on the remanufacturing option selected. We show the interdependencies among the plant selection, remanufacturing option and job scheduling when subject to resource constraints, which motivate the integrated solution proposed in this paper. The solution method is composed of the linear physical programming and the multi-level encoding genetic algorithm (GA). By performing a case study, we illustrate the use of the model and we present the resulting managerial insights. The results show that the proposed integrated approach performs better compared with the regular GA in terms of makespan.

Keywords:

• remanufacturing
• rework
• remanufacturing option
• linear physical programming
• genetic algorithm

Additional information

Funding

Funding. This work is sponsored by National Natural Science Foundation project [grant number 71101090]; Shanghai Top Academic Discipline Project-Management Science & Engineering, Doctoral Fund of the Ministry of Education [grant number 20133121110001]; Shanghai Yangfan Programme [grant number 14YF1411200]; Shanghai Municipal Education Commission Project [grant number 13YZ080], [grant number 14YZ112]; Shanghai Maritime University Research Project [grant number 20120102], [grant number 20120125].