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GENI Ants for the Traveling Salesman Problem

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Abstract

In this paper, the probabilistic nearest neighbor heuristic, which is at the core of classical ant colony systems for the Traveling Salesman Problem, is replaced by an alternative insertion procedure known as the GENI heuristic. The benefits provided by GENI-based ants are empirically demonstrated on a set of benchmark problems, through a comparison with the classical ant colony system and an iterated GENI heuristic.

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Authors and Affiliations

  1. Centre de recherche sur les transports Département d'informatique et de recherche opérationnelle, Université de Montréal, C.P. 6128, succursale Centre-ville, Montréal, Québec, Canada, H3C 3J7

    François-Xavier Le Louarn, Michel Gendreau & Jean-Yves Potvin

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  1. François-Xavier Le Louarn
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  2. Michel Gendreau
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  3. Jean-Yves Potvin
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Le Louarn, FX., Gendreau, M. & Potvin, JY. GENI Ants for the Traveling Salesman Problem. Ann Oper Res 131, 187–201 (2004). https://doi.org/10.1023/B:ANOR.0000039518.73626.a5

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  • DOI: https://doi.org/10.1023/B:ANOR.0000039518.73626.a5

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