Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/109116
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Type: | Conference paper |
Title: | A feature-based analysis on the impact of linear constraints for ε-constrained differential evolution |
Author: | Poursoltan, S. Neumann, F. |
Citation: | IEEE Transactions on Evolutionary Computation, 2014, pp.3088-3095 |
Publisher: | Institute of Electrical and Electronics Engineers |
Issue Date: | 2014 |
ISBN: | 9781479914883 |
ISSN: | 1089-778X 1941-0026 |
Conference Name: | 2014 IEEE Congress on Evolutionary Computation (CEC 2014) (6 Jul 2014 - 11 Jul 2014 : Beijing, China) |
Statement of Responsibility: | Shayan Poursoltan, Frank Neumann |
Abstract: | Feature-based analysis has provided new insights into what characteristics make a problem hard or easy for a given algorithms. Studies, so far, considered unconstrained continuous optimisation problem and classical combinatorial optimisation problems such as the Travelling Salesperson problem. In this paper, we present a first feature-based analysis for constrained continuous optimisation. To start the feature-based analysis of constrained continuous optimization, we examine how linear constraints can influence the optimisation behaviour of the wellknown e-constrained differential evolution algorithm. Evolving the coefficients of a linear constraint, we show that even the type of one linear constraint can make a difference of 10-30% in terms of function evaluations for well-known continuous benchmark functions. |
Keywords: | Constraints, continuous optimisation, difficulty prediction, linear constraints, features |
Rights: | © 2014 IEEE |
DOI: | 10.1109/CEC.2014.6900572 |
Grant ID: | http://purl.org/au-research/grants/arc/DP130104395 http://purl.org/au-research/grants/arc/DP140103400 |
Published version: | http://dx.doi.org/10.1109/cec.2014.6900572 |
Appears in Collections: | Aurora harvest 3 Computer Science publications |
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