Deep reinforcement learning for solving the heterogeneous capacitated vehicle routing problem

• Main Authors: LI, Jingwen, MA, Yining, GAO, Ruize, CAO, Zhiguang, LIM, Andrew, SONG, Wen, ZHANG, Jie
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Decoding; Search problems; Reinforcement learning; Computer architecture; Vehicle routing; Routing; Optimization; Deep reinforcement learning (DRL); heterogeneous CVRP (HCVRP); min-max objective; min-sum objective; Management Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/8204
• Institution: Singapore Management University

Existing deep reinforcement learning (DRL)-based methods for solving the capacitated vehicle routing problem (CVRP) intrinsically cope with a homogeneous vehicle fleet, in which the fleet is assumed as repetitions of a single vehicle. Hence, their key to construct a solution solely lies in the selec...