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Monte Carlo Vehicle Routing

Cazenave, Tristan; Lucas, Jean-Yves; Kim, Hyoseok; Triboulet, Thomas (2020), Monte Carlo Vehicle Routing, 11th International Workshop on Agents in Traffic and Transportation (ATT 2020) held in conjunction with ECAI 2020, 2020-08, Saint Jacques de Compostelle, Spain

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Type
Communication / Conférence
Date
2020
Conference title
11th International Workshop on Agents in Traffic and Transportation (ATT 2020) held in conjunction with ECAI 2020
Conference date
2020-08
Conference city
Saint Jacques de Compostelle
Conference country
Spain
Metadata
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Author(s)
Cazenave, Tristan
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Lucas, Jean-Yves
Kim, Hyoseok
Triboulet, Thomas
Abstract (EN)
Nested Rollout Policy Adaptation (NRPA) is a Monte Carlo search algorithm that learns a playout policy in order to solve a single player game. In this paper we apply NRPA to the vehicle routing problem. This problem is important for large companies that have to manage a fleet of vehicles on a daily basis. Real problems are often too large to be solved exactly. The algorithm is applied to standard problem of the literature and to the specific problems of EDF (Electricite De France, the main french electric utility company). These specific problems have peculiar constraints. NRPA gives better result than the algorithm previously used by EDF.
Subjects / Keywords
Monte Carlo Tree Search