A fast evolutionary algorithm for combinatorial optimization problems

Author

Yan, Xue-song ; Li, Hui ; Cai, Zhi-hua ; Kang, Li-shan

Author_Institution

Sch. of Comput. Sci., China Univ. of Geosci., Beijing, China

Volume

6

fYear

2005

fDate

18-21 Aug. 2005

Firstpage

3288

Abstract

In this paper we proposed a new algorithm based on inver-over operator, for combinatorial optimization problems. Inver-over is based on simple inversion; however, knowledge taken from other individuals in the population influences its action. In the new algorithm we use some new strategies including selection operator, replace operator and some new control strategy, which have been proved to be very efficient to accelerate the converge speed. Through the experiment, the new algorithm shows great efficiency in solving TSP with the problem scale under 300.

Keywords

genetic algorithms; travelling salesman problems; TSP; combinatorial optimization problem; evolutionary algorithm; genetic algorithm; inver-over operator; traveling salesman problem; Acceleration; Circuits; Computer aided instruction; Computer science; Dynamic programming; Evolutionary computation; Genetic algorithms; Geology; Heuristic algorithms; Traveling salesman problems; Evolutionary algorithm; Inver-over operator; genetic algorithm; traveling salesman problem;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on

Conference_Location

Guangzhou, China

Print_ISBN

0-7803-9091-1

Type

conf

DOI

10.1109/ICMLC.2005.1527510

Filename

1527510