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A Novel Algorithm to Scheduling Optimization of Melting-Casting Process in Copper Alloy Strip Production

Author

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  • Xiaohui Yan
  • Zhicong Zhang
  • Jianwen Guo
  • Shuai Li
  • Kaishun Hu

Abstract

Melting-casting is the first process in copper alloy strip production. The schedule scheme on this process affects the subsequent processes greatly. In this paper, we build the multiobjective model of melting-casting scheduling problem, which considers minimizing the makespan and total weighted earliness and tardiness penalties comprehensively. A novel algorithm, which we called Multiobjective Artificial Bee Colony/Decomposition (MOABC/D) algorithm, is proposed to solve this model. The algorithm combines the framework of Multiobjective Evolutionary Algorithm/Decomposition (MOEA/D) and the neighborhood search strategy of Artificial Bee Colony algorithm. The results on instances show that the proposed MOABC/D algorithm outperforms the other two comparison algorithms both on the distributions of the Pareto front and the priority in the optimal selection results.

Suggested Citation

  • Xiaohui Yan & Zhicong Zhang & Jianwen Guo & Shuai Li & Kaishun Hu, 2015. "A Novel Algorithm to Scheduling Optimization of Melting-Casting Process in Copper Alloy Strip Production," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-13, October.
    • Handle: RePEc:hin:jnddns:147980
    DOI: 10.1155/2015/147980
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    References listed on IDEAS

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    1. Ma, Lianbo & Hu, Kunyuan & Zhu, Yunlong & Chen, Hanning, 2015. "A hybrid artificial bee colony optimizer by combining with life-cycle, Powell’s search and crossover," Applied Mathematics and Computation, Elsevier, vol. 252(C), pages 133-154.
    2. Vargas, Luis G., 1990. "An overview of the analytic hierarchy process and its applications," European Journal of Operational Research, Elsevier, vol. 48(1), pages 2-8, September.
    3. Moslehi, Ghasem & Mahnam, Mehdi, 2011. "A Pareto approach to multi-objective flexible job-shop scheduling problem using particle swarm optimization and local search," International Journal of Production Economics, Elsevier, vol. 129(1), pages 14-22, January.
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