A NEW HYBRID GENETIC ALGORITHM FOR MAXIMUM INDEPENDENT SET PROBLEM

被引:0
|
作者
Mehrabi, Saeed [1 ]
Mehrabi, Abbas [2 ]
Mehrabi, Ali D. [3 ]
机构
[1] Shahid Bahonar Univ Kerman, Dept Comp Sci, Kerman, Iran
[2] Islamic Azad Univ, Dept Comp Engn, South Tehran Branch, Tehran, Iran
[3] Yazd Univ, Dept Math & Comp Sci, Yazd, Iran
关键词
Algorithmic Graph Theory; Combinatorial Optimization; Maximum Independent Set Problem; Genetic Algorithms;
D O I
暂无
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In recent years, Genetic Algorithms (GAs) have been frequently used for many search and optimization problems. In this paper, we use genetic algorithms for solving the NP-complete maximum independent set problem (MISP). We have developed a new heuristic independent crossover (HIX) especially for MISP, introducing a new hybrid genetic algorithm (MIS-HGA). We use a repair operator to ensure that our offsprings are valid after mutation. We compare our algorithm, MIS-GA, with an efficient existing algorithm called GENEsYs. Also, a variety of benchmarks are used to test our algorithm. As the experimental results show: 1) our algorithm outperforms GENEsYs, and, 2) applying HIX to genetic algorithms with an appropriate mutation rate, gives far better performance than the classical crossover operators.
引用
收藏
页码:314 / +
页数:2
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