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首页> 外文会议>Evolutionary computation in combinatorial optimization >Diversity Control and Multi-Parent Recombination for Evolutionary Graph Coloring Algorithms
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Diversity Control and Multi-Parent Recombination for Evolutionary Graph Coloring Algorithms

机译：进化图着色算法的分集控制和多亲子重组

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摘要

We present a hybrid evolutionary algorithm for the graph coloring problem (Evocol). Evocol is based on two simple-but-effective ideas. First, we use an enhanced crossover that collects the best color classes out of more than two parents; the best color classes are selected using a ranking based on both class fitness and class size. We also introduce a simple method of using distances to assure the population diversity: at each operation that inserts an individual into the population or that eliminates an individual from the population, Evocol tries to maintain the distances between the remaining individuals as large as possible. The results of Evocol match the best-known results from the literature on almost all difficult DIMACS instances (a new solution is also reported for a very large graph). Evocol obtains these performances with a success rate of at least 50%.
机译：我们提出了一种针对图着色问题（Evocol）的混合进化算法。 Evocol基于两个简单但有效的想法。首先，我们使用增强的分频器，该分频器从两个以上的父级中收集最佳的颜色分类；最好的颜色类别是使用基于类别适合度和类别大小的排名来选择的。我们还介绍了一种使用距离来确保种群多样性的简单方法：在将个体插入种群中或从种群中消除个体的每次操作中，Evocol都尝试将其余个体之间的距离保持尽可能大。 Evocol的结果与文献上几乎所有困难的DIMACS实例的最著名结果相吻合（对于非常大的图形，也报告了一种新的解决方案）。 Evocol获得这些表演的成功率至少为50％。

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