Thèse de Kassem Danach

Hyperheuristics in Logistics

Success in using exact methods for large scale combinatorial optimization is still limited to certain problems or to specific classes of instances of problems. The alternative way is either using metaheuristics or matheuristics that rely on exact methods in some ways. The concept of hyperheuristics (HH) is a generalization of that of metaheuristics. In the context of combinatorial optimization, we are interested in heuristics to choose heuristics invoked to solve the addressed problem. In this thesis, we focus on hyperheuristic optimization in logistic problems. We focus on proposing a hyperheuristic framework that carries out a search in the space of heuristic algorithms and learns how to change the incumbent heuristic in a systematic way along the process in such a way that a good sequence of heuristics produces high quality solutions. We propose HHs for two optimization problems in logistics: the workover rig scheduling problem and the hub location routing problem. Then, we compare the performances of several HHs described in the literature for the latter problem, which embed different heuristic selection methods such as a random selection, achoice function, a Q-Learning approach, and an ant colony based algorithm. The computational results prove the efficiency of HHs for the two problems in hand, and the relevance of including Lagrangian relaxation information for the second problem


Directeur de thèse : Frederic Semet, Professeur, Centrale Lille, Lille Rapporteurs : Adnan Yassine, Professeur, Université du Havre, Le Havre Reza Abdi, Lecturer, University of Bradford School of Management, Bradford Membres : Saïd Hanafi, Professeur, Université de Valenciennes et du Hainaut-Cambrésis, Valenciennes Laetitia Jourdan, Professeur, Université de Lille 1, Lille Abbas Tarhini, Assistant Professor, Lebanese American University, Beirut Rahimeh Neamatian Monemi, Chargé de Recherche, University Road, Southampton Wissam Khalil, Associate Professor, Lebanese University, Beirut Shahin Gelareh, Maître de Conférences, Réseaux et Télécommunications IUT de Béthune

Thèse de l'équipe INOCS soutenue le 21 décembre 2016

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