Leveraging Reinforcement Learning, Constraint Programming and Local Search: A Case Study in Car Manufacturing
| Autor: | Alain Nguyen, Valentin Antuori, Marie-José Huguet, Emmanuel Hebrard, Siham Essodaigui |
|---|---|
| Přispěvatelé: | Équipe Recherche Opérationnelle, Optimisation Combinatoire et Contraintes (LAAS-ROC), Laboratoire d'analyse et d'architecture des systèmes (LAAS), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, RENAULT, Lecture Notes in Computer Science, vol 12333, H. Simonis, ANR-19-P3IA-0004,ANITI,Artificial and Natural Intelligence Toulouse Institute(2019), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT) |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
050101 languages & linguistics
Mathematical optimization Computer science 05 social sciences Time horizon 02 engineering and technology Solver Travelling salesman problem Synthetic data [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] 0202 electrical engineering electronic engineering information engineering Constraint programming Local consistency Leverage (statistics) Reinforcement learning 020201 artificial intelligence & image processing 0501 psychology and cognitive sciences |
| Zdroj: | International Conference on Principles and Practice of Constraint Programming Principles and Practice of Constraint Programming. CP 2020 Principles and Practice of Constraint Programming. CP 2020, Sep 2020, Louvain La Neuve, Belgium. pp.657-672, ⟨10.1007/978-3-030-58475-7_38⟩ Lecture Notes in Computer Science ISBN: 9783030584740 CP |
| DOI: | 10.1007/978-3-030-58475-7_38⟩ |
| Popis: | International audience; The problem of transporting vehicle components in a car manufacturer workshop can be seen as a large scale single vehicle pickup and delivery problem with periodic time windows. Our experimental evaluation indicates that a relatively simple constraint model shows some promise and in particular outperforms the local search method currently employed at Renault on industrial data over long time horizon. Interestingly, with an adequate heuristic, constraint propagation is often sufficient to guide the solver toward a solution in a few backtracks on these instances. We therefore propose to learn efficient heuristic policies via reinforcement learning and to leverage this technique in several approaches: rapid-restarts, limited discrepancy search and multi-start local search. Our methods outperform both the current local search approach and the classical CP models on industrial instances as well as on synthetic data. |
| Databáze: | OpenAIRE |
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