自适应Jaya算法求解多目标柔性车间绿色调度问题
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江苏大学 管理学院,江苏 镇江 212013

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E-mail: jiannywang@163.com.

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TP301

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国家自然科学基金项目(71673118).


Multi-objective flexible job shop green scheduling problem with self-adaptive Jaya algorithm
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College of Management,Jiangsu University,Zhenjiang 212013,China

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    摘要:

    针对多目标柔性作业车间绿色调度问题(MO-FJGSP),建立优化目标为最大完工时间、机器总负荷和能耗最小的多目标数学模型,并设计一种基于Pareto最优解的自适应多目标Jaya算法(SAMO-Jaya)对该问题进行优化求解.算法采用两级实数编码方式实现工序排序与机器分配的编码表示,并设计一种转换机制实现将Jaya连续解空间映射至FJSP离散解空间;然后设计一种混沌序列与均匀分布相结合的混合策略以提高初始种群的质量与全局分散性;此外,在Jaya算法中嵌入自适应调整种群规模的方法以提高算法求解速度.通过10个单目标与3个多目标基准算例测试,并与7个已有算法进行对比分析,结果表明SAMO-Jaya算法能够对MO-FJGSP进行有效求解.

    Abstract:

    A mathematical model aiming at minimizing the makespan, total machine utilization and energy consumption is established according to the multi-objective flexible job shop green scheduling problem(MO-FJGSP). A self-adaptive multi-objective Jaya algorithm(SAMO-Jaya) based on Pareto optimal solution is designed to optimize the model. And two-level real number encoding is adopted to implement the coding scheme of processes' sequences and machines' assignment, then a transformation mechanism is designed to create a mapping between the continuous solution space of Jaya and the discrete solution space of flexible job-shop scheduling problem(FJSP). And then a hybrid strategy combining chaotic sequence and uniform distribution is raised to improve the quality and diversity of the initial populations. In addition, a self-adaptive population size adjusting method is embedded to improve the optimizing speed of the algorithm. By analyzing the solutions of 10 single-objective benchmarks and 3 multi-objective benchmarks solved by SAMO-Jaya and other 7 existing algorithms, the results show that SAMO-Jaya can solve the MO-FJGSP effectively.

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王建华,潘宇杰,孙瑞.自适应Jaya算法求解多目标柔性车间绿色调度问题[J].控制与决策,2021,36(7):1714-1722

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  • 在线发布日期: 2021-06-16
  • 出版日期: 2021-07-20
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