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Remanufacturing-oriented process planning and scheduling: mathematical modelling and evolutionary optimisation
Authors:Guiliang Gong  Raymond Chiong  Xuran Gong  Hezhiyuan Huang  Wenwu Han
Affiliation:1. State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, People’s Republic of China;2. School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, Australia "ORCIDhttps://orcid.org/0000-0002-8285-1903
Abstract:Remanufacturing has been widely studied for its potential to achieve sustainable production in recent years. In the literature of remanufacturing research, process planning and scheduling are typically treated as two independent parts. However, these two parts are in fact interrelated and often interact with each other. Doing process planning without considering scheduling related factors can easily introduce contradictions or even infeasible solutions. In this work, we propose a mathematical model of integrated process planning and scheduling for remanufacturing (IPPSR), which simultaneously considers the process planning and scheduling problems. An effective hybrid multi-objective evolutionary algorithm (HMEA) is presented to solve the proposed IPPSR. For the HMEA, a multidimensional encoding operator is designed to get a high-quality initial population. A multidimensional crossover operator and a multidimensional mutation operator are also proposed to improve the convergence speed of the algorithm and fully exploit the solution space. Finally, a specific legalising method is used to ‘legalise’ possible infeasible solutions generated by the initialisation method and mutation operator. Extensive computational experiments carried out to compare the HMEA with some well-known algorithms confirm that the proposed HMEA is able to obtain more and better Pareto solutions for IPPSR.
Keywords:remanufacturing oriented process planning and scheduling  remanufacturing  hybrid multi-objective evolutionary algorithm  multi-objective optimisation  Pareto front
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