Department   Hiroshima shudo University  The Faculty of Commercial Sciences
   Position   Professor
Language English
Publication Date 2020/11
Type Articles
Peer Review With peer review
Title Constrained Optimization by Improved Particle Swarm Optimization with the Equivalent Penalty Coefficient Method
Contribution Type Co-Authored Publication
Journal Artificial Life and Robotics
Journal TypeAnother Country
Publisher Springer
Volume, Issue, Pages 25(4),pp.612-623
Number of pages 12
Author and coauthor Tetsuyuki Takahama, Setsuko Sakai
Details In this study, we propose to apply the equivalent penalty coeffcient (EPC) method to particle swarm optimization (PSO) where a new solution is compared with the best solution found so far. In order to improve the performance of constrained optimization, a mutation operation is also proposed. The proposed method is examined using two topologies of PSO. The advantage of the proposed method is shown by solving well-known constrained optimization problems and comparing the results with those obtained by PSO with a standard constraint-handling technique.
DOI https://link.springer.com/article/10.1007/s10015-020-00653-z