An improved hybrid ant-local search algorithm for the partition graph coloring problem

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摘要

In this paper we propose a hybrid Ant Colony Optimization (ACO) algorithm for the Partition Graph Coloring Problem (PGCP). Given an undirected graph G=(V,E), whose nodes are partitioned into a given number of the sets, the goal of the PGCP is to find a subset V∗⊂V that contains exactly one node from each cluster and a coloring for V∗ so that in the graph induced by V∗, two adjacent nodes have different colors and the total number of used colors is minimal. Our hybrid algorithm is obtained by executing a local search procedure after every ACO iteration. The performance of our algorithm is evaluated on a set of instances commonly used as benchmark and the computational results show that compared to state-of-the-art algorithms, our improved hybrid ACO algorithm achieves solid results in very short run-times.

论文关键词:Partition graph coloring problem,Metaheuristics,Ant Colony Optimization,Local search

论文评审过程:Received 5 November 2014, Revised 20 March 2015, Available online 23 April 2015, Version of Record 8 September 2015.

论文官网地址:https://doi.org/10.1016/j.cam.2015.04.030