Associate Professor Tsung-Che Chiang

Department of Computer Science and Information Engineering
National Taiwan Normal University

Tel: +886-2-77346692    Fax: +886-2-29322378    Email

Yann-Chern Jou, Shuo-Ying Wang, Jia-Fong Yeh, and Tsung-Che Chiang, Multi-population modified L-SHADE for single objective bound constrained optimization, Proc. of IEEE Congress on Evolutionary Computation (CEC), Glasgow, UK (virtual conference due to COVID-19), Jul. 19-24, 2020.

• Full text: Official version, Unedited version
• Source code: GitHub

Abstract

In this paper, we extend a previous algorithm mL-SHADE by running the evolutionary process through multiple populations and adding dynamic control of mutation intensity and hyper-parameters. The whole population is partitioned into sub-populations by a random clustering method. Mutation intensity and hyper-parameters are adjusted based on the consumption of fitness function evaluations. Performance of the proposed algorithm is verified by ten benchmark functions in the CEC2020 Competition on Single Objective Bound Constrained Optimization. The results show the competitiveness of the proposed algorithm.

CEC2020 Competition Results

• The proposed mpmL-SHADE was the 7th place among 11 participants in the competition.

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