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An Improved Multiobjective PSO for the Scheduling Problem of Panel Block Construction

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  • Zhi Yang
  • Cungen Liu
  • Xuefeng Wang
  • Weixin Qian

Abstract

Uncertainty is common in ship construction. However, few studies have focused on scheduling problems under uncertainty in shipbuilding. This paper formulates the scheduling problem of panel block construction as a multiobjective fuzzy flow shop scheduling problem (FSSP) with a fuzzy processing time, a fuzzy due date, and the just‐in‐time (JIT) concept. An improved multiobjective particle swarm optimization called MOPSO‐M is developed to solve the scheduling problem. MOPSO‐M utilizes a ranked‐order‐value rule to convert the continuous position of particles into the discrete permutations of jobs, and an available mapping is employed to obtain the precedence‐based permutation of the jobs. In addition, to improve the performance of MOPSO‐M, archive maintenance is combined with global best position selection, and mutation and a velocity constriction mechanism are introduced into the algorithm. The feasibility and effectiveness of MOPSO‐M are assessed in comparison with general MOPSO and nondominated sorting genetic algorithm‐II (NSGA‐II).

Suggested Citation

  • Zhi Yang & Cungen Liu & Xuefeng Wang & Weixin Qian, 2016. "An Improved Multiobjective PSO for the Scheduling Problem of Panel Block Construction," Discrete Dynamics in Nature and Society, John Wiley & Sons, vol. 2016(1).
    • Handle: RePEc:wly:jnddns:v:2016:y:2016:i:1:n:5413520
    DOI: 10.1155/2016/5413520
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    References listed on IDEAS

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    1. A. R. Rahimi-Vahed & S. M. Mirghorbani, 2007. "A multi-objective particle swarm for a flow shop scheduling problem," Journal of Combinatorial Optimization, Springer, vol. 13(1), pages 79-102, January.
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