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Fitness Landscapes and Performance of Meta-Heuristics

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Meta-Heuristics

Abstract

We perform a statistical analysis of the structure of the search space of some planar, euclidian instances of the traveling salesman problem. We want to depict this structure from the point of view of iterated local search algorithms. The objective is two-fold: understanding the experimentally known good performance of metaheuristics on the TSP and other combinatorial optimization problems; designing new techniques to search the space more efficiently. This work actually led us to design a hybrid genetic algorithm that competes rather well with other local search heuristics for the TSP, notably Jünger et al.’s version of ILK. This work also opens promising horizons to the study of other combinatorial optimization problems such as the quadratic assignment problem.

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Fonlupt, C., Robilliard, D., Preux, P., Talbi, EG. (1999). Fitness Landscapes and Performance of Meta-Heuristics. In: Voß, S., Martello, S., Osman, I.H., Roucairol, C. (eds) Meta-Heuristics. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5775-3_18

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  • DOI: https://doi.org/10.1007/978-1-4615-5775-3_18

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-7646-0

  • Online ISBN: 978-1-4615-5775-3

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