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Discrete Dynamics in Nature and Society
Volume 2016 (2016), Article ID 5413520, 13 pages
Research Article

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

1State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
2Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration, Shanghai 200240, China

Received 1 February 2016; Revised 27 April 2016; Accepted 10 May 2016

Academic Editor: Seenith Sivasundaram

Copyright © 2016 Zhi Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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).