Integrated scheduling for remanufacturing system considering component commonality using improved multi-objective genetic algorithm

The existing researches on scheduling for remanufacturing system explicitly or implicitly subjects to the component matching requirements while ignoring the repaired component commonality, which is inconsistent with reality. Thus, this paper proposes a novel integrated scheduling method for remanufacturing system with disassembly-reprocessing-reassembly considering component commonality, where components obtained by reprocessing no longer only be used to reassemble their original product, but also be used to reassemble other remanufacturing products. And a mathematic model is formulated to simultaneously minimize the completion time and total energy consumption. Then, an improved multi-objective genetic algorithm (IMOGA) with a new double-layer representation scheme is developed to handle the considered problem. In the IMOGA, a left-shift strategy is developed to utilize workstation idle time and a component-relink strategy is designed to solve the reassembly decision with component commonality. In addition, the crossover and mutation operators based on grouping strategy are designed to enhance algorithm search ability. After, a local search with two heuristic strategies is proposed to further improve the quality of solutions in the elite set. Finally, a series of comparative experiments are carried out and the results show that IMOGA can tackle this scheduling problem effectively.

Automated summary

This paper proposes a novel integrated scheduling method for remanufacturing system, considering component commonality and minimizing completion time and total energy consumption. An improved multi-objective genetic algorithm (IMOGA) is developed to handle the problem, along with heuristic strategies for solution improvement. Comparative experiments demonstrate the effectiveness of IMOGA in tackling this scheduling problem.