Journal
APPLIED SOFT COMPUTING
Volume 37, Issue -, Pages 774-786Publisher
ELSEVIER
DOI: 10.1016/j.asoc.2015.09.007
Keywords
Evolutionary computation; Constrained optimization; Equality constraint reduction; Variable reduction
Categories
Funding
- Singapore National Research Foundation (NRF) under its Campus for Research Excellence and Technological Enterprise (CREATE) programme
- Cambridge Advanced Research Centre in Energy Efficiency in Singapore (CARES) [C4T]
- National Natural Science Foundation of China [61563016, 41571397, 51178193]
Ask authors/readers for more resources
Efficient constraint handling techniques are of great significance when Evolutionary Algorithms (EAs) are applied to constrained optimization problems (COPs). Generally, when use EAs to deal with COPs, equality constraints are much harder to satisfy, compared with inequality constraints. In this study, we propose a strategy named equality constraint and variable reduction strategy (ECVRS) to reduce equality constraints as well as variables of COPs. Since equality constraints are always expressed by equations, ECVRS makes use of the variable relationships implied in such equality constraint equations. The essence of ECVRS is it makes some variables of a COP considered be represented and calculated by some other variables, thereby shrinking the search space and leading to efficiency improvement for EAs. Meanwhile, ECVRS eliminates the involved equality constraints that providing variable relationships, thus improves the feasibility of obtained solutions. ECVRS is tested on many benchmark problems. Computational results and comparative studies verify the effectiveness of the proposed ECVRS. (C) 2015 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available