Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/109188
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Type: Conference paper
Title: A feature-based analysis on the impact of set of constraints for ε-constrained differential evolution
Author: Poursoltan, S.
Neumann, F.
Citation: Proceedings of the 22nd International Conference on Neural Information Processing, 2015 / Arik, S., Huang, T., Lai, W., Liu, Q. (ed./s), vol.9491, iss.Part III, pp.344-355
Publisher: Springer
Issue Date: 2015
Series/Report no.: Lecture Notes in Computer Science (LNCS, vol. 9491)
ISBN: 9783319265544
ISSN: 0302-9743
1611-3349
Conference Name: 22nd International Conference on Neural Information Processing (ICONIP 2015) (09 Nov 2015 - 12 Nov 2015 : Istanbul, Turkey)
Statement of
Responsibility: 
Shayan Poursoltan and Frank Neumann
Abstract: Different types of evolutionary algorithms have been developed for constrained continuous optimisation. We carry out a featurebased 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 epsilon-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.
Rights: © Springer International Publishing Switzerland 2015
RMID: 0030041421
DOI: 10.1007/978-3-319-26555-1_39
Grant ID: http://purl.org/au-research/grants/arc/DP130104395
http://purl.org/au-research/grants/arc/DP140103400
Appears in Collections:Computer Science publications

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