A deep reinforcement learning approach for the meal delivery problem

作者：

Highlights：

• Our MDP model for the courier assignment task characterizes on-demand meal delivery service.

• We tailor deep reinforcement learning algorithms to address the problem in a dynamic environment.

• We incorporate the notion of order rejection to reduce the number of late orders.

• We investigate the importance of intelligent repositioning of the couriers during their idle times.

摘要

•Our MDP model for the courier assignment task characterizes on-demand meal delivery service.•We tailor deep reinforcement learning algorithms to address the problem in a dynamic environment.•We incorporate the notion of order rejection to reduce the number of late orders.•We investigate the importance of intelligent repositioning of the couriers during their idle times.

论文关键词：Meal delivery,Courier assignment,Reinforcement learning,DQN,DDQN

论文评审过程：Received 1 April 2021, Revised 17 February 2022, Accepted 19 February 2022, Available online 25 February 2022, Version of Record 9 March 2022.

论文官网地址：https://doi.org/10.1016/j.knosys.2022.108489