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Constrained optimization problem solving using estimation of distribution algorithms

机译:使用分布估计算法求解约束优化问题

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Two variants of estimation of distribution algorithm (EDA) are tested solving several continuous optimization problems with constraints. Numerical experiments are conducted and comparison is made between constraint handling using several types of penalty and repair operators in case of both elitist and nonelitist implementation of the EDA's. Graphical display and animations of representative runs of the best and worst performers proved useful in enhancing the understanding of how such algorithms work.
机译:测试了分布估计算法(EDA)的两种变体,解决了一些带有约束的连续优化问题。进行了数值实验,并在使用EDA的精英和非精英两种情况下,使用几种类型的惩罚运算符和修复运算符对约束处理进行了比较。表现最佳和最差的代表运行的图形显示和动画被证明有助于增进对此类算法工作原理的理解。

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