Abstract
Different types of evolutionary algorithms have been developed for constrained continuous optimisation. We carry out a feature based analysis of evolved constrained continuous optimisation instances to understand the characteristics of constraints that make problems hard for evolutionary algorithm. In our study, we examine how various sets of constraints can influence the behaviour of ε-Constrained Differential Evolution. Investigating the evolved instances, we obtain knowledge of what type of constraints and their features make a problem difficult for the examined algorithm.
Cite
CITATION STYLE
Poursoltan, S., & Neumann, F. (2015). A feature-based analysis on the impact of set of constraints for ε-constrained differential evolution. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9491, pp. 344–355). Springer Verlag. https://doi.org/10.1007/978-3-319-26555-1_39
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