A matheuristic algorithm for solving the vehicle routing problem with cross-docking

• Main Authors: GUNAWAN, Aldy, WIDJAJA, Audrey Tedja, VANSTEENWEGEN, Pieter, YU, Vincent F.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Vehicle routing problem; Cross-docking; Scheduling; Matheuristic; Artificial Intelligence and Robotics; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/5265; https://ink.library.smu.edu.sg/context/sis_research/article/6268/viewcontent/Gunawan2020_Chapter_AMatheuristicAlgorithmForSolvi.pdf
• Institution: Singapore Management University

This paper studies the integration of the vehicle routing problem with cross-docking, namely VRPCD. The aim is to find a set of routes to deliver single products from a set of suppliers to a set of customers through a cross-dock facility, such that the operational and transportation costs are minimized, without violating the vehicle capacity and time horizon constraints. A two-phase matheuristic approach that uses the routes of the local optima of an adaptive large neighborhood search (ALNS) as columns in a set-partitioning formulation of the VRPCD is designed. This matheuristic outperforms the state-of-the-art algorithms in solving a subset of benchmark instances.