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On the population diversity control of evolutionary algorithms for production scheduling problems

机译:生产调度问题进化算法的种群多样性控制

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In the literature, many evolutionary algorithms have been proposed for the production scheduling problems such as genetic algorithm, particle swarm optimization, differential evolution, and so on. However, these algorithms mainly focus on the efficiency of local search methods but seldom tackle the control of population diversity. Therefore, this paper aims to check whether the population diversity control strategy can significantly impact the performance of evolutionary algorithms for the production scheduling problems. With this aim in mind, a population diversity control strategy was proposed and applied in a basic evolutionary algorithm. The computational results on two representative production scheduling problems, i.e., the single machine scheduling and the permutation flowshop scheduling, show that the proposed population diversity control strategy can significantly improve the basic evolutionary algorithm and that this algorithm with the strategy (but without local search) can even be competitive with other powerful evolutionary algorithms with local search in the literature.
机译:在文献中,针对遗传算法,粒子群优化,差分进化等,针对生产调度问题提出了许多进化算法。但是,这些算法主要集中在局部搜索方法的效率上,却很少解决人口多样性的控制问题。因此,本文旨在检查种群多样性控制策略是否可以显着影响生产调度问题的进化算法的性能。考虑到这一目标,提出了一种种群多样性控制策略,并将其应用于基本的进化算法中。对两个典型的生产调度问题(单机调度和置换流水车间调度)的计算结果表明,所提出的种群多样性控制策略可以显着改进基本的进化算法,并且该算法具有该策略(但无需局部搜索)甚至可以通过文献中的局部搜索与其他强大的进化算法竞争。

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