A New Genetic Algorithm for Graph Coloring

Raja Marappan, Gopalakrishnan Sethumadhavan
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引用次数: 26

Abstract

Graph coloring problem is a classical example for NP-hard combinatorial optimization. Solution to this graph coloring problem often finds its applications to various engineering fields. This paper exhibits the robustness of genetic algorithm to solve a graph coloring. The proposed genetic algorithm employs an innovative single parent conflict gene crossover and a conflict gene mutation as its operators. The time taken to get a convergent solution of this proposed genetic method has been compared with the existing approaches and has been proved to be effective. The performance of this approximation method is evaluated using some benchmarking graphs, and are found to be competent.
一种新的图着色遗传算法
图的着色问题是NP-hard组合优化的一个经典例子。这种图形着色问题的解决方法经常在各种工程领域中得到应用。本文证明了遗传算法在求解图着色问题中的鲁棒性。该遗传算法采用一种创新的单亲冲突基因交叉和冲突基因突变作为算子。通过与现有遗传方法的比较,证明了该遗传方法的有效性。用一些基准图对该近似方法的性能进行了评价,结果表明该方法是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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