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Autoencoder-based generation of individuals in population-based metaheuristics

Bastien Pasdeloup 1, 2 Maryam Karimi-Mamaghan 2, 1 Mehrdad Mohammadi 1, 2 Patrick Meyer 1, 2
1 Lab-STICC_IMTA_CID_DECIDE
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : In this work, we explore a new way of breeding individuals in a population-based metaheuristic, by exploiting the ability of autoencoders to interpolate representation of candidate solutions in a learned latent space. In the remaining of this document, we present in more details our idea and show its application to the traveling salesman problem.
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Submitted on : Thursday, March 12, 2020 - 10:56:44 AM
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Bastien Pasdeloup, Maryam Karimi-Mamaghan, Mehrdad Mohammadi, Patrick Meyer. Autoencoder-based generation of individuals in population-based metaheuristics. ROADEF 2020 : 21ème Congrès Annuel de la Société Française de Recherche Opérationnelle et d’Aide à la Décision, Feb 2020, Montpellier, France. ⟨hal-02506195⟩

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