期刊
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
卷 56, 期 11, 页码 3795-3814出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207543.2018.1425015
关键词
operation sequencing; discrete particle swarm optimisation; feasible operation sequences; adaptive mutation; Taguchi method
资金
- National Science Foundation of China [51575108, 71671035]
Operation sequencing is one of crucial tasks for process planning in a CAPP system. In this study, a novel discrete particle swarm optimisation (DPSO) named feasible sequence oriented DPSO (FSDPSO) is proposed to solve the operation sequencing problems in CAPP. To identify the process plan with lowest machining cost efficiently, the FSDPSO only searches the feasible operation sequences (FOSs) satisfying precedence constraints. In the FSDPSO, a particle represents a FOS as a permutation directly and the crossover-based updating mechanism is developed to evolve the particles in discrete feasible solution space. Furthermore, the fragment mutation for altering FOS and the uniform and greedy mutations for changing machine, cutting tool and tool access direction for each operation, along with the adaptive mutation probability, are adopted to improve exploration ability. Case studies are used to verify the performance of the FSDPSO. For case studies, the Taguchi method is used to determine the key parameters of the FSDPSO. A comparison has been made between the result of the proposed FSDPSO and those of three existing PSOs, an existing genetic algorithm and two ant colony algorithms. The comparative results show higher performance of the FSDPSO with respect to solution quality for operation sequencing.
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