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
TypeCommunication / Conférence
Conference title11th International Workshop on Agents in Traffic and Transportation (ATT 2020) held in conjunction with ECAI 2020
Conference citySaint Jacques de Compostelle
MetadataShow full item record
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
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 / KeywordsMonte Carlo Tree Search
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