Title: Effective allele preservation by offspring selection: an empirical study for the TSP

Authors: Michael Affenzeller, Stefan Wagner, Stephan M. Winkler

Addresses: Heuristic and Evolutionary Algorithms Laboratory, School of Informatics, Communications and Media Upper Austrian University of Applied Sciences, Softwarepark 11, A-4232 Hagenberg, Austria. ' Heuristic and Evolutionary Algorithms Laboratory, School of Informatics, Communications and Media Upper Austrian University of Applied Sciences, Softwarepark 11, A-4232 Hagenberg, Austria. ' Heuristic and Evolutionary Algorithms Laboratory, School of Informatics, Communications and Media Upper Austrian University of Applied Sciences, Softwarepark 11, A-4232 Hagenberg, Austria

Abstract: The basic selection ideas of the different representatives of evolutionary algorithms are sometimes quite diverse. The selection concept of Genetic Algorithms (GAs) and Genetic Programming (GP) is basically realised by the selection of above-average parents for reproduction, whereas Evolution Strategies (ES) use the fitness of newly evolved offspring as the basis for selection (survival of the fittest due to birth surplus). This contribution considers aspects of population genetics and ES in order to propose an enhanced and generic selection model for GAs which is able to preserve the alleles which are part of a high quality solution. Some selected aspects of these enhanced techniques are discussed exemplarily on the basis of the Travelling Salesman Benchmark (TSP) problem instances.

Keywords: soft computing; evolutionary computation; genetic algorithms; GAs selection; self adaptation; genetic programming; population genetics; evolution strategies; modelling; allele preservation; offspring selection; travelling salesman problem.

DOI: 10.1504/IJSPM.2010.032655

International Journal of Simulation and Process Modelling, 2010 Vol.6 No.1, pp.29 - 39

Received: 01 Oct 2008
Accepted: 15 Jan 2009
Published online: 11 Apr 2010 *

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