The parameter-less genetic algorithm in practice

Authors:
Fernando G. Lobo;David E. Goldberg
Affiliations:
Area Departamental de Engenharia Electrónica e Computação, FCT, Universidade do Algarve, Campus de Gambelas, 8000 Faro, Portugal;Department of General Engineering, University of Illinois at Urbana-Champaign, Urbana, IL
Venue:
Information Sciences—Informatics and Computer Science: An International Journal
Year:
2004

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Abstract

The parameter-less genetic algorithm was introduced a couple of years ago as a way to simplify genetic algorithm operation by incorporating knowledge of parameter selection and population sizing theory in the genetic algorithm itself. This paper shows how that technique can be used in practice by applying it to a network expansion problem. The existence of the parameter-less genetic algorithm stresses the fact that some problems need more processing power than others. Such observation leads to the development of a problem difficulty measure which is also introduced in this paper. The measure can be useful for comparing the difficulty of real-world problems.