JACIII Vol.23 No.4 pp. 758-766
doi: 10.20965/jaciii.2019.p0758


Designation of Candidate Solutions in Differential Evolution Based on Bandit Algorithm and its Evaluation

Masaya Sakakibara, Akira Notsu, Seiki Ubukata, and Katsuhiro Honda

Osaka Prefecture University
1-1 Gakuen-cho, Nakaku, Sakai, Osaka 599-8531, Japan

February 20, 2018
March 6, 2019
July 20, 2019
optimization algorithm, differential evolution, upper confidence bounds, UCB applied to trees
Result of DE initialized by UCT

Result of DE initialized by UCT

We propose UCT-Grid Area Search (UCT-GAS), which is an efficient optimization method that roughly estimates specific values in areas, and consider exploration and exploitation in optimization problems. This approach divides the search space and imagines it to be a multi-armed bandit, which enables us to use bandit algorithms to solve mathematical programming problems. Although the search speed is fast than other search algorithm like differential evolution, it might converge to a local solution. In this study, we improve this algorithm by replacing its random search part with differential evolution after several searches. Comparative experiments confirmed the search ability of the optimal solution, and our method benefits by showing that it avoids falling into a local solution and that its search speed is fast.

Cite this article as:
M. Sakakibara, A. Notsu, S. Ubukata, and K. Honda, “Designation of Candidate Solutions in Differential Evolution Based on Bandit Algorithm and its Evaluation,” J. Adv. Comput. Intell. Intell. Inform., Vol.23 No.4, pp. 758-766, 2019.
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