A Hybrid Evolutionary Approach for Multicriteria Optimization Problems: Application to the Flow Shop
A Hybrid Evolutionary Approach for Multicriteria Optimization Problems: Application to the Flow Shop
复制标题
多标准优化问题的混合进化方法：在流程车间中的应用
DOI：
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发表时间：
2001
期刊：
影响因子：
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通讯作者：
Clarisse Dhaenens
中科院分区：
文献类型：
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作者：
El;M. Rahoual;Mohamed;Clarisse Dhaenens
在许多工业领域，解决车间问题（例如流动厂或车间）的解决方案非常重要。优化的标准通常是makepan或迟到的最小化。但是，很少有人同时考虑到这些不同标准的方法。本文提出了一种基于适合多标准案例的混合遗传算法的方法。提出了几种选择和多样性的策略。使用不同的基准评估和比较他们的性能。还针对混合元启发式化提出了并行模型。它允许增加人口规模和世代数量，然后导致更好的结果。
The resolution of workshop problems such as the Flow Shop or the Job Shop has a great importance in many industrial areas. The criteria to optimize are generally the minimization of the makespan or the tardiness. However, few are the resolution approaches that take into account those different criteria simultaneously. This paper presents an approach based on hybrid genetic algorithms adapted to the multicriteria case. Several strategies of selection and diversity maintaining are presented. Their performances are evaluated and compared using different benchmarks. A parallel model is also proposed and implemented for the hybrid metaheuristic. It allows to increase the population size and the number of generations, and then leads to better results.