Opportunities for reinforcement learning in stochastic dynamic vehicle routing

There has been a paradigm-shift in urban logistic services in the last years; demand for real-time, instant mobility and delivery services grows. This poses new challenges to logistic service providers as the underlying stochastic dynamic vehicle routing problems (SDVRPs) require anticipatory real-t...

Full description

Bibliographic Details

Published in:	Computers & operations research Vol. 150; p. 106071
Main Authors:	Hildebrandt, Florentin D., Thomas, Barrett W., Ulmer, Marlin W.
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.02.2023
Subjects:	Approximate dynamic programming Combinatorial optimization Mixed integer programming Reinforcement learning Stochastic dynamic vehicle routing Survey Stochastic dynamic vehicle routing Approximate dynamic programming Mixed integer programming Survey Combinatorial optimization Reinforcement learning
ISSN:	0305-0548, 1873-765X
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!