Evolutionary Genetic Algorithms in a Constraint Satisfaction Problem: Puzzle Eternity II

Authors:
Jorge Muñoz;German Gutierrez;Araceli Sanchis
Affiliations:
University Carlos III of Madrid, Leganés, Spain 28911;University Carlos III of Madrid, Leganés, Spain 28911;University Carlos III of Madrid, Leganés, Spain 28911
Venue:
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Year:
2009

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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.