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|Title:||Experimental supplements to the computational complexity analysis of genetic programming for problems modelling isolated program semantics|
|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|
|Series/Report no.:||Lecture Notes in Computer Science; 7491|
|Conference Name:||International Conference on Parallel Problem Solving from Nature (12th : 2012 : Taormina, Italy)|
|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|
|Appears in Collections:||Computer Science publications|
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