Title :
Solving Multimodal problems by Coincidence Algorithm
Author :
Waiyapara, Kiatsopon ; Chongstitvatana, Prabhas
Author_Institution :
Dept. of Comput. Eng., Chulalongkorn Univ., Bangkok, Thailand
fDate :
May 30 2012-June 1 2012
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;
Conference_Titel :
Computer Science and Software Engineering (JCSSE), 2012 International Joint Conference on
Conference_Location :
Bangkok
Print_ISBN :
978-1-4673-1920-1
DOI :
10.1109/JCSSE.2012.6261923
