Feature-based selection of bio-inspired algorithms for constrained continuous optimisation
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Date
2016
Authors
Poursoltan, Shayan
Editors
Advisors
Neumann, Frank
Michalewicz, Zbigniew
Michalewicz, Zbigniew
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Abstract
Constrained continuous optimisation problems are widespread in the real-world and often very complex. Bio-inspired algorithms such as evolutionary algorithms (EAs) or particle swarm optimisation (PSO) algorithms have been successful in solving these problems. Recently, there has been an increasing interest in understanding the features of problems that make them hard to solve. These studies have been carried out for discrete and unconstrained continuous optimisation problems, to find the relationship between problem features and algorithm performance. To study the connection between algorithms and constrained optimisation problems (COPs), more practical perspectives of problem features analysis and their relations to algorithms are essential. Thus, this thesis contributes to the understanding of constrained optimisation problems and their constraint features that make them hard to solve by algorithms. We introduce an empirical feature-based analysis for COPs and bio-inspired algorithms. Furthermore, the relationships between the constraint features of given COPs and algorithms are studied here. By linking the features of the constraints and different bio-inspired algorithms, we design a new model for predicting the algorithm performance for COPs based on their constraint features. In this thesis, we present a novel approach to analyse constrained continuous optimisation problems based on their constraint features. Furthermore we use this knowledge to implement an automated feature-based algorithm selection model for constrained continuous optimisation.
School/Discipline
School of Computer Science
Dissertation Note
Thesis (Ph.D.) (Research by Publication) -- University of Adelaide, School of Computer Science, 2016.
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This electronic version is made publicly available by the University of Adelaide in accordance with its open access policy for student theses. Copyright in this thesis remains with the author. This thesis may incorporate third party material which has been used by the author pursuant to Fair Dealing exceptions. If you are the owner of any included third party copyright material you wish to be removed from this electronic version, please complete the take down form located at: http://www.adelaide.edu.au/legals