Evaluation of a Self-Organizing Migrating Algorithm applied to discrete event simulation optimization

P. Raška, Zdeněk Ulrych
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引用次数: 1

Abstract

The paper deals with testing and evaluation of a modified Self-Organizing Migrating Algorithm (SOMA) applied to a discrete event simulation model reflecting the supply of production lines using automated guided vehicles. The SOMA heuristic optimization method is derived from the Differential Evolution method. We test all the SOMA strategies under the same conditions of the simulation experiments - the same termination criteria, number of repetitions in the optimization experiments, and the same setting of the basic parameters of the SOMA. We propose a methodology using different evaluation criteria to analyse the different SOMA strategies behaviour of finding the optimum of an objective function specified for each discrete event simulation model.
一种应用于离散事件模拟优化的自组织迁移算法的评价
本文研究了一种改进的自组织迁移算法(SOMA),并将其应用于反映自动引导车辆生产线供应的离散事件仿真模型。SOMA启发式优化方法是由差分进化方法衍生而来的。我们在相同的模拟实验条件下测试了所有的SOMA策略——相同的终止准则,优化实验的重复次数,以及相同的SOMA基本参数设置。我们提出了一种方法,使用不同的评估标准来分析不同的SOMA策略行为,以找到为每个离散事件模拟模型指定的目标函数的最优值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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