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A Hybrid Genetic Algorithm for Cell Formation Problems Using Operational Time

机译:一种使用操作时间的细胞形成问题的混合遗传算法

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This paper presents a two-stage approach consisting of a real-coded genetic algorithm and goal programming to obtain improved cell formation. In the first stage, the minimum value of each objective is determined using a single-objective genetic algorithm. In the second stage, goal programming is incorporated and the final objective is constructed as the minimization of sum of devia-tional variables of corresponding objectives. The proposed technique is implemented as a software toolkit using C Sharp.net programming language. Modified grouping efficiency is used as the performance measure to test the efficiency of the proposed technique. Five problems with different sizes have been considered from the literature to show the potentials of the proposed technique.
机译:本文提出了一种两级方法,包括实际编码的遗传算法和目标编程,以获得改善的细胞形成。在第一阶段,使用单目标遗传算法确定每个目的的最小值。在第二阶段,结合了目标编程,并且最终目标被构造为相应目标的脱硫变量总和的最小化。使用C sharp.NET编程语言,所提出的技术实现为软件工具包。改进的分组效率用作测试所提出的技术效率的性能措施。从文献中考虑了不同尺寸的五个问题,以显示所提出的技术的潜力。

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