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

Zhi Yang, Cungen Liu, Xuefeng Wang and Weixin Qian

Discrete Dynamics in Nature and Society, 2016, vol. 2016, 1-13

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).

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnddns:5413520

DOI: 10.1155/2016/5413520

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