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    崔喆, 顾幸生. 求解中间存储有限Flow Shop调度问题的离散群搜索优化算法[J]. 华东理工大学学报(自然科学版), 2013, (6): 713-719.
    引用本文: 崔喆, 顾幸生. 求解中间存储有限Flow Shop调度问题的离散群搜索优化算法[J]. 华东理工大学学报(自然科学版), 2013, (6): 713-719.
    CUI Zhe, GU Xing-sheng. A Discrete Group Search Optimizer for Flow Shop Scheduling Problem with Limited Buffers[J]. Journal of East China University of Science and Technology, 2013, (6): 713-719.
    Citation: CUI Zhe, GU Xing-sheng. A Discrete Group Search Optimizer for Flow Shop Scheduling Problem with Limited Buffers[J]. Journal of East China University of Science and Technology, 2013, (6): 713-719.

    求解中间存储有限Flow Shop调度问题的离散群搜索优化算法

    A Discrete Group Search Optimizer for Flow Shop Scheduling Problem with Limited Buffers

    • 摘要: 针对中间存储有限的Flow Shop调度问题,提出了一种离散群搜索优化算法来最小化工件加工的总流水时间。该算法首先采用基于工件排列的离散编码方式,使得能够直接求解离散的调度问题;其次提出了新的初始化方法,确保了初始种群既具有一定的多样性,又有较好的性能;还引入了离散差分进化的思想,增强了算法的运算效率与搜索能力。最后使用正交设计的方法设置算法参数,通过对Taillard算例的仿真计算,验证了本文算法的优越性。

       

      Abstract: Aming at the Flow Shop scheduling problem with limited buffers (LBFSP), this paper proposes a discrete group search optimizer (DGSO) algorithm to minimize the total flow time. The DGSO algorithm adopts the job permutation based representation to enable the continuous group search optimizer algorithm to be used in the scheduling problems directly. And then, a new initialization way is developed to guarantee the initial population with a certain quality and diversity. Moreover, the discrete differential evolution scheme is integrated to improve the algorithm performance. In addition, an orthogonal design is utilized to adjust the parameters of the DGSO algorithm. The simulation results via Taillard benchmark show the effectiveness of the proposed algorithm.

       

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