Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/77311
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Type: Conference paper
Title: Experimental supplements to the computational complexity analysis of genetic programming for problems modelling isolated program semantics
Author: Urli, T.
Wagner, M.
Neumann, F.
Citation: Proceedings of the 12th International Conference on Parallel Problem Solving from Nature, held in Taormina, Italy 1-5 September, 2012 / C.A. Coello Coello, V. Cutello, K. Deb, S. Forrest, G. Nicosia and M. Pavone (eds.): pp.102-112
Publisher: Springer-Verlag
Publisher Place: Germany
Issue Date: 2012
Series/Report no.: Lecture Notes in Computer Science; 7491
ISBN: 9783642329364
ISSN: 0302-9743
1611-3349
Conference Name: International Conference on Parallel Problem Solving from Nature (12th : 2012 : Taormina, Italy)
Statement of
Responsibility: 
Tommaso Urli, Markus Wagner and Frank Neumann
Abstract: In this paper, we carry out experimental investigations that complement recent theoretical investigations on the runtime of simple genetic programming algorithms [3, 7]. Crucial measures in these theoretical analyses are the maximum tree size that is attained during the run of the algorithms as well as the population size when dealing with multi-objective models. We study those measures in detail by experimental investigations and analyze the runtime of the different algorithms in an experimental way.
Keywords: Genetic programming; problem complexity; multiple objective optimization; experimental evaluation
Rights: © Springer-Verlag Berlin Heidelberg 2012
RMID: 0020122233
DOI: 10.1007/978-3-642-32937-1_11
Published version: https://doi.org/10.1007/978-3-642-32937-1
Appears in Collections:Computer Science publications

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