A hybrid algorithm for solving generalized class cover problem

Authors:
Yanxin Huang;Chunguang Zhou;Yan Wang;Yongli Bao;Yin Wu;Yuxin Li
Affiliations:
Institute of Genetics and Cytology, Northeast Normal University, Changchun, China;College of Computer Science and Technology, Jilin University, Changchun, China;College of Computer Science and Technology, Jilin University, Changchun, China;Institute of Genetics and Cytology, Northeast Normal University, Changchun, China;Institute of Genetics and Cytology, Northeast Normal University, Changchun, China;Institute of Genetics and Cytology, Northeast Normal University, Changchun, China
Venue:
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Year:
2006

Citing 3
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Abstract

A generalized class cover problem is presented in this article, and then reduced to a constrained multi-objective optimization problem. Solving this problem is significantly important to construct a robust classification system. Therefore, three algorithms for solving the generalized class cover problem are proposed, which are greedy algorithm, binary particle swarm optimization algorithm, and their hybrid algorithm. Comparison results of these three methods show that the hybrid algorithm can get better solutions in less runtime.