Solving Multimodal problems by Coincidence Algorithm

Author

Waiyapara, Kiatsopon ; Chongstitvatana, Prabhas

Author_Institution

Dept. of Comput. Eng., Chulalongkorn Univ., Bangkok, Thailand

fYear

2012

fDate

May 30 2012-June 1 2012

Firstpage

45

Lastpage

48

Abstract

In general, Multimodal optimization is hard problems even for Evolutionary Algorithm. Using a Genetic Algorithm (GA) to solve these problems, the algorithm cannot converge to solutions easily. This work presents a study of Coincidence Algorithm (COIN) to solve these problems. COIN has an ability to retain multiple solutions in its model; hence it is suitable for Multimodal optimization problems. The experiment is carried out to illustrate this capability. The benchmarks are designed for comparing the problem solving behavior of COIN against a Genetic Algorithm.

Keywords

genetic algorithms; COIN; GA; coincidence algorithm; evolutionary algorithm; genetic algorithm; multimodal optimization problem; multimodal problems; Algorithm design and analysis; Benchmark testing; Evolutionary computation; Genetic algorithms; Optimization; Probabilistic logic; Traveling salesman problems; Coincidence Algorithm; Genetic Algorithm; Multimodal Problem;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Software Engineering (JCSSE), 2012 International Joint Conference on

Conference_Location

Bangkok

Print_ISBN

978-1-4673-1920-1

Type

conf

DOI

10.1109/JCSSE.2012.6261923

Filename

6261923