Assembly sequence planning for aerospace products based on particle swarm optimization and genetic algorithm

Dan Zhang, Dun Wen Zuo, Guang Ming Jiao, Shan Liang Xue, Jian Ping Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)

Abstract

In order to solve the assembly sequence planning for aerospace products (ASPFAP), which is multi-objective, non-linear and difficult to be solved by the traditional algorithms of ASP, a new method was presented based on particle swarm optimization and genetic algorithm (PSO-GA). The assembly precedence constraint relationship model (APCRM) was studied; the code representations of genomes, chromosomes and particles were studied; the fitness function with engineering significance was presented by comprehensive consideration of assembly continuity, assembly resource and influence of instrument and equipment; the geometric feasible assembly sequences were initialized according to the APCRM and optimized based on PSO-GA in which the GA's crossover operator was reconstructed by PSO. An application case was studied to demonstrate good convergence, stability and actual engineering significance of the proposed algorithm.

Original languageEnglish
Pages (from-to)1228-1234
Number of pages7
JournalBinggong Xuebao/Acta Armamentarii
Volume31
Issue number9
Publication statusPublished - Sept 2010
Externally publishedYes

Keywords

  • Assembly precedence constraint relationship model
  • Assembly sequence planning
  • Crossover operator
  • Machinofacture technique and equipment
  • Particle swarm optimization and genetic algorithm

ASJC Scopus subject areas

  • Mechanical Engineering

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