Article ID: | iaor200972066 |
Country: | United Kingdom |
Volume: | 40 |
Issue: | 11 |
Start Page Number: | 1031 |
End Page Number: | 1049 |
Publication Date: | Nov 2008 |
Journal: | Engineering Optimization |
Authors: | Zahara Erwie, Hu Chia-Hsin |
Constrained optimization problems (COPs) are very important in that they frequently appear in the real world. A COP, in which both the function and constraints may be nonlinear, consists of the optimization of a function subject to constraints. Constraint handling is one of the major concerns when solving COPs with particle swarm optimization (PSO) combined with the Nelder-Mead simplex search method (NM-PSO). This article proposes embedded constraint handling methods, which include the gradient repair method and constraint fitness priority-based ranking method, as a special operator in NM-PSO for dealing with constraints. Experiments using 13 benchmark problems are explained and the NM-PSO results are compared with the best known solutions reported in the literature. Comparison with three different meta-heuristics demonstrates that NM-PSO with the embedded constraint operator is extremely effective and efficient at locating optimal solutions.