Department   Hiroshima shudo University  The Faculty of Commercial Sciences
   Position   Professor
Language English
Publication Date 2019/06
Type Articles
Peer Review With peer review
Title An Equivalent Penalty Coefficient Method: An Adaptive Penalty Approach for Population-Based Constrained Optimization
Contribution Type Co-Authored Publication
Journal Proceedings of 2019 IEEE Congress on Evolutionary Computation
Journal TypeAnother Country
Publisher IEEE
Volume, Issue, Pages 1,pp.1621-1628
Number of pages 8
Author and coauthor Tetsuyuki Takahama and Setsuko Sakai
Details The penalty function method has been widely used for solving constrained optimization problems. In the method, an extended objective function, which is the sum of the objective value and the constraint violation weighted by the penalty coeffi-cient, is optimized. However, it is difficult to control the coefficient properly because proper control of the coefficient varies in each problem. In this study, the equivalent penalty coefficient value (EPC) is proposed for population-based optimization algorithms (POAs). EPC can be defined in POAs where a new solution is compared with the old solution. EPC is the penalty coefficient value that makes the two extended objective values of the solutions the same. Search that gives priority to the objective value is realized by selecting a small EPC. Search that gives priority to the constraint violation is realized by selecting a large EPC. The adaptive control of the penalty coefficient can be realized by selecting an appropriate EPC.
DOI 10.1109/CEC.2019.8790360