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A two-stage interactive evolutionary algorithm for multi-objective asynchronous parallel selective disassembly sequence planning problem
DOI:10.1016/j.cie.2022.108855.png)
摘要
En 中文
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.
Keyword:
Selective disassembly sequence planning
Asynchronous parallel disassembly
Profit -oriented and energy -efficient tasks
assignment
Two -stage interactive evolutionary algorithm
期刊
IF:
6.5
论文数:
1.0W
被引数:
3.8W
机构
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