A two-stage interactive evolutionary algorithm for multi-objective asynchronous parallel selective disassembly sequence planning problem. (January 2023)

• Record Type: Journal Article
• Authors: Sun, Xiang; Guo, Shunsheng; Guo, Jun; Du, Baigang
• Is Part Of: Computers & industrial engineering. Volume 175(2023)
• Publication Date: 2023-01
• Subjects: Selective disassembly sequence planning -- Asynchronous parallel disassembly -- Profit-oriented and energy-efficient tasks assignment -- Two-stage interactive evolutionary algorithm; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108855
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: The work develops a multi-objective asynchronous parallel SDSP model without synchronization requirement between tasks. PEAPSDSP model can consume less disassembly time and energy, and gain more disassembly profit compared with traditional model. A two-stage interactive evolutionary algorithm is developed for the proposed model. The proposed TS-IMOEA shows better superiorities than other comparison algorithms. Abstract: The existing studies of selective disassembly sequence planning (SDSP) focus on sequential SDSP, which is inefficient especially when disassembling complex products. Moreover, energy efficiency has not received much attention in SDSP, which is the critical manifestation of environmental impact. Thus, this work focuses on parallel SDSP and further proposes a profit-oriented and energy-efficient multi-objective asynchronous parallel SDSP (PEAPSDSP) for optimizing disassembly time, energy consumption, and disassembly profit simultaneously. In PEAPSDSP, multiple components can be removed simultaneously and without synchronization requirement. Then, a two-stage interactive multi-objective evolutionary algorithm (TS-IMOEA) is proposed to address PEAPSDSP. The potential non-dominated solutions (NDSs) are obtained in first stage, and a novel search strategy is designed to further improve the quality of NDSs and population quality in second stage. Numerical results in three different scale cases demonstrate the superiority of TS-IMOEA in solving PEAPSDSP, and the benefit of considering selective disassembly in value recovery.