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A Discrete Bat Algorithm for Disassembly Sequence Planning 被引量:6

A Discrete Bat Algorithm for Disassembly Sequence Planning
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摘要 Based on the bat algorithm(BA), this paper proposes a discrete BA(DBA) approach to optimize the disassembly sequence planning(DSP) problem, for the purpose of obtaining an optimum disassembly sequence(ODS) of a product with a high degree of automation and guiding maintenance operation. The BA for solving continuous problems is introduced, and combining with mathematical formulations, the BA is reformed to be the DBA for DSP problems. The fitness function model(FFM) is built to evaluate the quality of disassembly sequences. The optimization performance of the DBA is tested and verified by an application case, and the DBA is compared with the genetic algorithm(GA), particle swarm optimization(PSO) algorithm and differential mutation BA(DMBA). Numerical experiments show that the proposed DBA has a better optimization capability and provides more accurate solutions than the other three algorithms. Based on the bat algorithm(BA), this paper proposes a discrete BA(DBA) approach to optimize the disassembly sequence planning(DSP) problem, for the purpose of obtaining an optimum disassembly sequence(ODS) of a product with a high degree of automation and guiding maintenance operation. The BA for solving continuous problems is introduced, and combining with mathematical formulations, the BA is reformed to be the DBA for DSP problems. The fitness function model(FFM) is built to evaluate the quality of disassembly sequences. The optimization performance of the DBA is tested and verified by an application case, and the DBA is compared with the genetic algorithm(GA), particle swarm optimization(PSO) algorithm and differential mutation BA(DMBA). Numerical experiments show that the proposed DBA has a better optimization capability and provides more accurate solutions than the other three algorithms.
作者 JIAO Qinglong XU Da 焦庆龙;徐达(Department of Arms Engineering, Academy of Armored Force Engineering)
出处 《Journal of Shanghai Jiaotong university(Science)》 EI 2018年第2期276-285,共10页 上海交通大学学报(英文版)
关键词 disassembly sequence planning(DSP) bat algorithm(BA) discrete BA(DBA) fitness function model(FFM) genetic algorithm(GA) particle swarm optimization(PSO) algorithm differential mutation BA(DMBA) disassembly sequence planning (DSP), bat algorithm (BA), discrete BA (DBA), fitness function model (FFM), genetic algorithm (GA), particle swarm optimization (PSO) algorithm, differential mutation BA (DMBA)
作者简介 E-mail: jql1988@sina.cn
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