Formele, exacte en metaheuristische methodes voor combinatorische optimalisatie
Notice bibliographique
Résumé
Combinatorial optimization problems are ubiquitous in real life and hence a wide range of solving paradigms are available. Each paradigm has its own characteristics, which are potentially complementary. Therefore, investigating the possibility to combine different approaches might be beneficial for solving combinatorial problems. This dissertation exploits this research theme at two different levels. The first part of this dissertation exploits the relationships between solving paradigms at a general level. We investigate the combination of two sub-domains of Operations Research and Artificial Intelligence, namely Local Search and Knowledge Representation. We propose "declarative local search", which allows for specifying local search heuristics declaratively. Declarative local search is built on top of IDP, a Knowledge Base System. IDP consists of a set of inference methods for solving different tasks around a center knowledge base described in the formal language FO(·), an extension of first-order logic. Declarative local search enables local search heuristics to be synthesized from their formal descriptions. The framework has been proven empirically to be able to serve as a fast prototype tool for local search heuristics and also to function as an alternative back-end for some combinatorial problems that are traditionally difficult for formal systems such as IDP. In the second part, we study two particular combinatorial problems and how different solving methods are utilized to solve them. The first case study, namely the Intermittent Travelling Salesman Problem, presented in chapter 4, is a new variant of the Travelling Salesman Problem. The problem is inspired by real-world drilling/texturing applications where the temperature of the work-piece is taken into account. An exact branch-and-bound approach and four Variable Neighbourhood Search metaheuristics are proposed. The problem's characteristics are analyzed and an instance library is created and made publicly available for future research. The second case study, namely the Radiotherapy Scheduling Problem, presented in chapter 5, is a real scheduling problem at CHUM, a large cancer center in Montréal, Canada. We propose a two-phase approach where Mixed Integer Programming and Constraint Programming models are proposed for each phase. The algorithm is tested on a realistic dataset generated from real data provided by CHUM. The results show the dominance of a non-conventional Constraint Programming approach over the conventional Mathematical Programming for the problem. Summarized, the two parts of this dissertation investigate the relationships between solving paradigms at two complementary levels. We investigate the combined use of and the interaction between very different methodologies in a common domain of application.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».