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多目标Jaya算法求解节能柔性作业车间调度问题

Multi-Objective Jaya Algorithm for Solving Energy-Saving Flexible Job Shop Scheduling Problem
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摘要 在实际的柔性作业车间调度中,考虑工件运输时间和机器可选速度的影响,建立了优化最大完工时间、机器总负载和加工过程总能耗的多目标优化模型,并提出了一种改进的多目标Jaya算法用于求解该模型。结合问题的特点,采用了一种包含工序、机器和速度的三层编码和考虑运输时间和机器速度的插入式解码,并采用多种规则的混合策略的初始化种群方法以提高种群质量,然后根据不同情况设计多种不同的离散个体更新方式,并基于问题的特点设计了5种邻域结构,以提高算法的搜索能力。最后,在对基准算例改造并进行对比实验,验证了所提算法的可行性与有效性。 In the actual flexible job shop scheduling, considering the influence of transportation time and ma-chine speed, a multi-objective optimization model is established to optimize the maximum comple-tion time, machine tool load and total energy consumption of the machining process, and an im-proved multi-objective Jaya algorithm is proposed for solving the model, considering the effects of workpiece transport time and machine optional speed on the scheduling results. Combining the characteristics of the problem, a three-level coding containing process, machine and speed and an insertion decoding considering transport time and machine speed, and a hybrid strategy of multi-ple rules are used to initialise the population approach to improve the population quality, and then a variety of different discrete individual update methods are designed according to different situa-tions, and five neighbourhood structures are designed based on the characteristics of the problem to improve the search capability of the algorithm. Finally, the feasibility and effectiveness of the proposed algorithm is verified after modifying the benchmark algorithm and conducting compari-son experiments.
出处 《建模与仿真》 2023年第3期1850-1865,共16页 Modeling and Simulation
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