Journal of Shanghai Jiao Tong University (Science) ›› 2018, Vol. 23 ›› Issue (2): 276-285.doi: 10.1007/s12204-018-1937-6

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A Discrete Bat Algorithm for Disassembly Sequence Planning

A Discrete Bat Algorithm for Disassembly Sequence Planning

JIAO Qinglong (焦庆龙), XU Da (徐达)   

  1. (Department of Arms Engineering, Academy of Armored Force Engineering, Beijing 100072, China)
  2. (Department of Arms Engineering, Academy of Armored Force Engineering, Beijing 100072, China)
  • Online:2018-04-01 Published:2018-06-19
  • Contact: JIAO Qinglong (焦庆龙) E-mail:jql1988@sina.cn

Abstract: 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.

Key words: 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)

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.

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)

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