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 language | English |
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Pages (from-to) | 1228-1234 |
Number of pages | 7 |
Journal | Binggong Xuebao/Acta Armamentarii |
Volume | 31 |
Issue number | 9 |
Publication status | Published - Sept 2010 |
Externally published | Yes |
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