A novel evolutionary algorithm for MCP using MEC

Author

Sun, C.Y. ; Li, W.J. ; Gao, X.Z.

Author_Institution

Artificial Intelligence Inst., Beijing City Univ., China

fYear

2005

fDate

28-30 June 2005

Firstpage

99

Lastpage

104

Abstract

A novel evolutionary algorithm for the maximum clique problem (MCP) is presented in the paper. That is called MCP-MEC1 and is based on mind evolutionary computation (MEC). The construction of individuals, groups, operations-similartaxis and dissimilation and the evaluation of individuals are accomplished for MCP. 21 benchmark graphs collected by DIMACS (Discrete Mathematics and Theoretical Computer Science) are used to evaluate the performance of the MCP-MEC1 algorithm. The results obtained by MCP-MEC1 are compared with those obtained by two best algorithms for the MCP, RLS (reactive local search) and HGA (heuristic based genetic algorithm). It is shown that the MCP-MEC1 outperforms HGA and is as good as RLS. So the MCP-MEC1 is one of the best heuristic algorithms for the MCP.

Keywords

genetic algorithms; graph theory; heuristic programming; search problems; DIMACS; Discrete Mathematics and Theoretical Computer Science; HGA; MCP-MEC1; RLS; evolutionary algorithm; heuristic based genetic algorithm; maximum clique problem; mind evolutionary computation; reactive local search; Artificial intelligence; Computer science; Evolutionary computation; Genetic algorithms; Heuristic algorithms; Mathematics; Paper technology; Power electronics; Resonance light scattering; Sun;

fLanguage

English

Publisher

ieee

Conference_Titel

Soft Computing in Industrial Applications, 2005. SMCia/05. Proceedings of the 2005 IEEE Mid-Summer Workshop on

Print_ISBN

0-7803-8942-5

Type

conf

DOI

10.1109/SMCIA.2005.1466955

Filename

1466955