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A multi-objective hybrid evolutionary approach for buffer allocation in open serial production lines

机译:打开串行生产线缓冲分配的多目标混合进化方法

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摘要

The buffer allocation problem is of particular interest for operations management since buffers have a considerable impact on capacity improvement in production systems. In this study, the buffer allocation is solved to optimize two conflicting objectives of maximizing the average system production rate and minimizing total buffer size. A hybrid evolutionary algorithm-based simulation optimization approach is proposed for the multi-objective buffer allocation problem (MOBAP) in open serial production lines. As a search methodology, the Pareto optimal set is derived by hybrid approach using elitist non-dominated sorting genetic algorithm (NSGA-II) and a special version of a multi-objective simulated annealing. As an evaluative tool, discrete event simulation modeling is used to estimate the performance measures for the production systems. To demonstrate the efficacy of the proposed hybrid approach, a comparative study is provided for the MOBAP in various serial line configurations. The comparative results show that the hybrid method has a considerable potential to minimize the total buffer space by appropriately allocating space to each buffer while maximizing average production rate.
机译:缓冲区分配问题对于操作管理特别感兴趣,因为缓冲器对生产系统的能力改进具有相当大的影响。在这项研究中,缓冲区分配得到解决,以优化两个相互矛盾的目标,最大化平均系统生产率并最小化总缓冲尺寸。基于混合进化算法的仿真优化方法是为开放式串行生产线中的多目标缓冲区分配问题(Mobap)。作为搜索方法,Pareto最佳集由混合方法使用Elitist非主导的分类遗传算法(NSGA-II)和多目标模拟退火的特殊版本来导出。作为评估工具,离散事件仿真建模用于估计生产系统的性能措施。为了证明所提出的混合方法的功效,在各种串行配置中为MODAP提供了比较研究。比较结果表明,混合方法具有相当大的潜力,可以通过适当地分配给每个缓冲器的空间,同时最小化总缓冲空间,同时最大化平均生产率。

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