A Novel ABC Optimization Algorithm for Graph Coloring Problem

R. S. Tomar, Sonali Singh, S. Verma, G. Tomar
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引用次数: 9

Abstract

In this paper, graph coloring has been done using artificial bee colony (ABC) optimization algorithm. Graph coloring deals with the challenge of coloring the nodes of any graph by least possible number of colors while ensuring on same time that two adjacent nodes does not gain same color. That least possible count of colors used denotes the chromatic number of a graph and to determine this number for any graph is an NP-complete problem hence no existing polynomial time algorithm can solve it. To find the best coloring sequence, a large search space has to be explored. Graph coloring deals with the challenge of coloring the nodes of any graph by least possible number of colors while ensuring on same time that two adjacent nodes does not gain same color and proposed a novel artificial bee colony (ABC) optimization algorithm for graph coloring. In this paper, we analyzed the proposed algorithm and compared it with three other graph coloring algorithms i.e. first fit, largest degree based ordering (LDO) and saturation degree based ordering (SDO). These results also indicate that ABC algorithm converges in a few iterations and is able to optimally allocate colors to vertices of a graph.
图着色问题的ABC优化算法
本文采用人工蜂群(ABC)优化算法对图进行着色。图着色处理的挑战是用尽可能少的颜色为任意图的节点着色,同时确保相邻的两个节点不获得相同的颜色。最小可能使用的颜色数表示图的色数,确定任何图的色数是一个np完全问题,因此没有现有的多项式时间算法可以解决。为了找到最佳的着色序列,必须探索一个大的搜索空间。图的着色问题是在保证相邻的两个节点颜色不相同的同时,用尽可能少的颜色对任意图的节点进行着色,提出了一种新的图的人工蜂群(ABC)优化算法。在本文中,我们分析了所提出的算法,并将其与其他三种图着色算法即首次拟合、基于最大度排序(LDO)和基于饱和度排序(SDO)进行了比较。这些结果也表明ABC算法在几次迭代中收敛,并且能够最优地为图的顶点分配颜色。
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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