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A Novel MOEA/D for Multiobjective Scheduling of Flexible Manufacturing Systems

Author

Listed:
  • Xinnian Wang
  • Keyi Xing
  • Chao-Bo Yan
  • Mengchu Zhou

Abstract

This paper considers the multiobjective scheduling of flexible manufacturing systems (FMSs). Due to high degrees of route flexibility and resource sharing, deadlocks often exhibit in FMSs. Manufacturing tasks cannot be finished if any deadlock appears. For solving such problem, this work develops a deadlock-free multiobjective evolutionary algorithm based on decomposition (DMOEA/D). It intends to minimize three objective functions, i.e., makespan, mean flow time, and mean tardiness time. The proposed algorithm can decompose a multiobjective scheduling problem into a certain number of scalar subproblems and solves all the subproblems in a single run. A type of a discrete differential evolution (DDE) algorithm is also developed for solving each subproblem. The mutation operator of the proposed DDE is based on the hamming distance of two randomly selected solutions, while the crossover operator is based on Generalization of Order Crossover. Experimental results demonstrate that the proposed DMOEA/D can significantly outperform a Pareto domination-based algorithm DNSGA-II for both 2-objective and 3-objective problems on the studied FMSs.

Suggested Citation

  • Xinnian Wang & Keyi Xing & Chao-Bo Yan & Mengchu Zhou, 2019. "A Novel MOEA/D for Multiobjective Scheduling of Flexible Manufacturing Systems," Complexity, Hindawi, vol. 2019, pages 1-14, June.
    • Handle: RePEc:hin:complx:5734149
    DOI: 10.1155/2019/5734149
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    References listed on IDEAS

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    2. Libin Han & Keyi Xing & Xiao Chen & Fuli Xiong, 2018. "A Petri net-based particle swarm optimization approach for scheduling deadlock-prone flexible manufacturing systems," Journal of Intelligent Manufacturing, Springer, vol. 29(5), pages 1083-1096, June.
    3. Dariush Khezrimotlagh & Yao Chen, 2018. "The Optimization Approach," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 107-134, Springer.
    4. Alejandro Alvarado-Iniesta & Jorge L. García-Alcaraz & Manuel Piña-Monarrez & Luis Pérez-Domínguez, 2016. "Multiobjective optimization of torch brazing process by a hybrid of fuzzy logic and multiobjective artificial bee colony algorithm," Journal of Intelligent Manufacturing, Springer, vol. 27(3), pages 631-638, June.
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