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A parallel tabu search for solving the primal buffer allocation problem in serial production systems

机译:并行禁忌搜索,用于解决批量生产系统中的原始缓冲区分配问题

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This paper presents a novel parallel tabu search (PTS) algorithm equipped with a proper adaptive neighborhood generation mechanism to solve the primal buffer allocation problem, which consists of minimizing the total buffer capacity of a serial production system under a minimum throughput rate constraint. An evaluative method based on a specific algorithm has been implemented to simulate the system behavior. In order to validate the effectiveness of the proposed PTS a mixed integer linear programming-based simulation/optimization approach and several metaheuristics from the relevant literature have been implemented. Since most metaheuristics are sensitive to the parameter setting, a proper calibration analysis based on a non-parametric test has been performed. Then, a comprehensive comparison analysis, concerning with both quality of solutions and computational efficiency, has been carried out. Finally, through the numerical results obtained from PTS, a multi-factorial experimental analysis has been developed to analyze the influencing factors of the problem under investigation. (C) 2015 Elsevier Ltd. All rights reserved.
机译:本文提出了一种新颖的并行禁忌搜索(PTS)算法,该算法配备了适当的自适应邻域生成机制来解决原始缓冲区分配问题,该算法包括在最小吞吐速率约束下使串行生产系统的总缓冲区容量最小化。已经实现了一种基于特定算法的评估方法来模拟系统行为。为了验证所提出的PTS的有效性,已经实施了基于混合整数线性规划的仿真/优化方法以及相关文献中的几种元启发法。由于大多数元启发法对参数设置敏感,因此已经执行了基于非参数测试的正确校准分析。然后,对解决方案的质量和计算效率进行了全面的比较分析。最后,通过从PTS获得的数值结果,进行了多因素实验分析,以分析所调查问题的影响因素。 (C)2015 Elsevier Ltd.保留所有权利。

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