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

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.