Modeling and Optimizing for Multi-objective Partial Disassembly Line Balancing Problem

doi:10.3901/JME.2018.03.125

Abstract

Abstract: Aiming at the disassembly characteristics of only considering the parts in demand and the hazardous parts in the actual production, a multi-objective mathematical model of the partial disassembly line balancing problem is constructed including the workstation number, smooth rate and disassembly cost three optimization objectives. And a Pareto based particle swarm algorithm incorporated with variable neighborhood is proposed considering the discrete nature of the solution and multiple optimization objectives. The mapping relationship between the disassembly tasks and the particle swarm iterative search is structured and the variable neighborhood search method is incorporated as the local search strategy in the proposed algorithm. To deal with the multiple objectives for the problem, the Pareto solution set and the crowding distance evaluation mechanism is introduced to ensure the diversity of the solution results. In addition, the Hyper-volume indicator is used to overcome the difficulty in evaluating the algorithm convergence performance and the Pareto muster in solving the multi-objective optimization problems. The superiority of the proposed algorithm is verified by different scale test cases of complete disassembly line balancing problem, and the contrast experiments show that the change of search depth of the proposed algorithm owns excellent performance the quality and computation efficiency. Finally, the proposed mathematical model and the presented algorithm is applied to the partial disassembly line design of a certain type of printer.

Key words: disassembly line balancing problem, Hyper-volume indicators, partial disassembly, particle swarm optimization algorithm, variable neighborhood search

CLC Number:

TH165
TP301

LI Liuke, ZHANG Zeqiang, ZHU Lixia, ZOU Binsen. Modeling and Optimizing for Multi-objective Partial Disassembly Line Balancing Problem[J]. Journal of Mechanical Engineering, 2018, 54(3): 125-136.

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