On feasible and infeasible search for equitable graph coloring

被引:5
作者
Sun, Wen [1 ]
Hao, Jin-Kao [1 ,4 ]
Lai, Xiangjing [2 ]
Wu, Qinghua [3 ]
机构
[1] Univ Angers, 2 Bd Lavoisier, Angers 49045, France
[2] Nanjing Univ Posts & Telecommun, 66 Xinmofan Rd, Nanjing 210023, Peoples R China
[3] Huazhong Univ Sci & Technol, 1037 Luoyu Rd, Wuhan 430074, Peoples R China
[4] Inst Univ France, Paris, France
来源
PROCEEDINGS OF THE 2017 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO'17) | 2017年
关键词
Equitable coloring; tabu search; heuristics; penalty-based fitness function; ALGORITHM;
D O I
10.1145/3071178.3071267
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
An equitable legal k-coloring of an undirected graph G = (V, E) is a partition of the vertex set V into k disjoint independent sets, such that the cardinalities of any two independent sets differ by at most one (this is called the equity constraint). As a variant of the popular graph coloring problem (GCP), the equitable coloring problem (ECP) involves finding a minimum k for which an equitable legal k-coloring exists. In this paper, we present a study of searching both feasible and infeasible solutions with respect to the equity constraint. The resulting algorithm relies on a mixed search strategy exploring both equitable and inequitable colorings unlike existing algorithms where the search is limited to equitable colorings only. We present experimental results on 73 DIMACS and COLOR benchmark graphs and demonstrate the competitiveness of this search strategy by showing 9 improved best-known results (new upper bounds).
引用
收藏
页码:369 / 376
页数:8
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