A New Genetic Algorithm for the Maximum Clique Problem

被引：0
|
作者：
Evin, Gozde Kizilates [1 ]
机构：
[1] Ege Univ, Fac Sci, Dept Math, Izmir, Turkey
来源：
ARTIFICIAL INTELLIGENCE AND APPLIED MATHEMATICS IN ENGINEERING PROBLEMS | 2020年 / 43卷
关键词：
Maximum clique problem; Graph theory; Optimization problems; Heuristic algorithms; Hybrid genetic algorithms; BOUND ALGORITHM; SEARCH;
D O I：
10.1007/978-3-030-36178-5_66
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The Maximum Clique Problem is widely studied optimization problem and plays an essential part in computer science. In the literature, therefore, there are many exact and heuristic approaches and new strategies are continuously being proposed. In this paper, the maximum clique problem is studied, and a new hybrid genetic algorithm is proposed for finding the maximum clique in a graph. The proposed algorithm is tested on the DIMACS and BHOSLIB benchmark instances. The computational results are compared with similar literature researches. The results prove the effectiveness of proposed algorithm.
引用
收藏
页码：766 / 774
页数：9
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