Adelaide Research & Scholarship
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https://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) |
| Editor: | Coello, C.A.C. Cutello, V. Deb, K. Forrest, S. Nicosia, G. Pavone, M. |
| 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 |
| DOI: | 10.1007/978-3-642-32937-1_11 |
| Published version: | http://dx.doi.org/10.1007/978-3-642-32937-1_11 |
| Appears in Collections: | Aurora harvest Computer Science publications |
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