Solving Capacitated and Time-constrained Vehicle Routing Problems by Deep Reinforcement Learning-based Method

Y. P. Tsang, Daniel Y. Mo, K. T. Chung, C. K.M. Lee

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

The Capacitated and Time-Constrained Vehicle Routing Problem (CTCVRP) is regarded as a complex but essential, optimization mission in logistics and transportation systems. In this paper, we propose a novel approach to use deep reinforcement learning to solve the CTCVRP in an e-fulfilment center environment. Our approach aims to deal with both capacity and time constraints, ensuring optimal resource allocation and timely deliveries. Deep reinforcement learning algorithms are developed in Python environment to guide the learning agent towards optimal decisions while satisfying constraints. Experimental evaluations on benchmarking instances demonstrate the viability and effectiveness of our approach, surpassing state-of-the-art techniques in terms of solution quality and computational efficiency. The contributions of this work include a reinforcement learning formulation for CTCVRP, a deep reinforcement learning-based approach and experimental analysis. This research provides a scalable and adaptable solution for solving capacitated and time-constrained vehicle routing problems with high practicality in a real-life environment.

Original languageEnglish
Title of host publication2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1578-1582
Number of pages5
ISBN (Electronic)9798350323153
DOIs
Publication statusPublished - Dec 2023
Event2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023 - Singapore, Singapore
Duration: 18 Dec 202321 Dec 2023

Publication series

Name2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023

Conference

Conference2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023
Country/TerritorySingapore
CitySingapore
Period18/12/2321/12/23

Keywords

  • algorithms
  • Deep reinforcement learning
  • logistics network
  • optimisation
  • vehicle routing problem

ASJC Scopus subject areas

  • Artificial Intelligence
  • Decision Sciences (miscellaneous)
  • Statistics, Probability and Uncertainty
  • Industrial and Manufacturing Engineering
  • Modelling and Simulation
  • Strategy and Management

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