中国机械工程 ›› 2015, Vol. 26 ›› Issue (11): 1478-1487.

• 智能制造 • 上一篇    下一篇

基于多目标混合殖民竞争算法的设备维护与车间调度集成优化

宋文家1;张超勇1;尹勇2;邵新宇1   

  1. 1.华中科技大学数字制造装备与技术国家重点实验室,武汉,430074
    2.武汉理工大学湖北省数字制造重点实验室,武汉,430070
  • 出版日期:2015-06-10 发布日期:2015-06-05
  • 基金资助:
    国家自然科学基金资助重点项目(51035001 );国家自然科学基金资助项目(51275190 );中央高校基本科研业务费资助项目(2014TS038)

Integrated Optimization of Equipment Maintenance and Shop Scheduling Problem Based on Multi-objective Hybrid Imperialist Competitive Algorithm

Song Wenjia1;Zhang Chaoyong1;Ying Yong2;Shao Xinyu1   

  1. 1.State Key Laboratory of Digital Manufacturing Equipment and Technology,Huazhong University of Science and Technology, Wuhan, 430074
    2.Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks,Wuhan University of Technology, Wuhan, 430070
  • Online:2015-06-10 Published:2015-06-05
  • Supported by:
    National Natural Science Foundation of China(No. 51035001, 51275190);Fundamental Research Funds for the Central Universities( No. 2014TS038 )

摘要:

在制定调度计划时考虑设备预防性维护可以提高设备利用率和资产效率。首先,依据实际制造车间生产环境,在每台机器的可靠度降低到阈值的时候安排预防性维护,建立柔性作业车间设备预防性维护与调度集成优化的数学模型,以最小化最大完工时间、总生产成本和平均总维修成本为目标。然后,提出一种多目标混合殖民竞争算法求解该模型,设计相应的编码、解码、殖民国家同化过程以及多目标混合殖民竞争算法的流程,并采用改进加权TOPSIS方法在获得的Pareto解集中选择满意解,以达到提高设备的可靠性、按期交货和节省成本的目的。最后通过具体实例验证提出策略的可行性和有效性。

关键词: 柔性作业车间调度问题, 预防性维护, 多目标混合殖民竞争算法, 多目标优化

Abstract:

In order to improve equipment utilization rate and maximize the efficiency of assets, preventive maintenance should be considered in production plan.A mathematical model to optimize the integrated flexible job shop equipment preventive maintenance and scheduling problem was established based on the real environment of the manufacturing shop with three objectives, including minimizing makespan, production cost, and average maintenance cost. An improved algorithm, which was referred to MOHICA, was proposed to solve the problem. This paper designed the process of encoding, decoding and empire assimilation as well as the procedure of MOHICA.An improved weighted TOPSIS (technique for order preference by similarity to an ideal solution) method was employed to choose the most satisfactory solution in the Pareto-optimal solutions to achieve the purposes of improving the reliability of the equipment, in-time delivery and saving cost. To validate the proposed strategy, an experimental test on a real-world instance was conducted. The computational results indicate that the proposed model is feasible and the algorithm is effective.

Key words: flexible job shop scheduling problem, preventive maintenance, multi-objective hybrid imperialist competitive algorithm(MOHICA), multi-objective optimization

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