Abstract
This paper evaluates a genetic algorithm and a multiobjective evolutionary algorithm in a constraint satisfaction problem (CSP). The problem that has been chosen is the Eternity II puzzle (E2), an edge-matching puzzle. The objective is to analyze the results and the convergence of both algorithms in a problem that is not purely multiobjective but that can be split into multiple related objectives. For the genetic algorithm two different fitness functions will be used, the first one as the score of the puzzle and the second one as a combination of the multiobjective algorithm objectives.
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Muñoz, J., Gutierrez, G., Sanchis, A. (2009). Evolutionary Genetic Algorithms in a Constraint Satisfaction Problem: Puzzle Eternity II. In: Cabestany, J., Sandoval, F., Prieto, A., Corchado, J.M. (eds) Bio-Inspired Systems: Computational and Ambient Intelligence. IWANN 2009. Lecture Notes in Computer Science, vol 5517. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02478-8_90
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DOI: https://doi.org/10.1007/978-3-642-02478-8_90
Publisher Name: Springer, Berlin, Heidelberg
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