Title :

A column generation based heuristic for the generalized vehicle routing problem with time windows

Author(s) :

Yuan, Yuan [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Cattaruzza, Diego [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Ogier, Maxime [Auteur]
Integrated Optimization with Complex Structure [INOCS]
SEMET, Frédéric [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Vigo, Daniele [Auteur]
Alma Mater Studiorum University of Bologna [UNIBO]

Journal title :

Transportation Research Part E: Logistics and Transportation Review

Pages :

102391

Publisher :

Elsevier

Publication date :

2021

ISSN :

1366-5545

English keyword(s) :

generalized vehicle routing problem
time windows
last mile delivery
delivery options
trunk/in-car delivery

HAL domain(s) :

Informatique [cs]/Recherche opérationnelle [cs.RO]

English abstract : [en]

The generalized vehicle routing problem with time windows (GVRPTW) is defined on a directed graph G = (V, A) where the vertex set V is partitioned into clusters. One cluster contains only the depot, where is located a ...
Show more >The generalized vehicle routing problem with time windows (GVRPTW) is defined on a directed graph G = (V, A) where the vertex set V is partitioned into clusters. One cluster contains only the depot, where is located a homogeneous fleet of vehicles, each with a limited capacity. The other clusters represent customers. A demand is associated with each cluster. Inside a cluster, the vertices represent the possible locations of the customer. A time window is associated with each vertex, during which the visit must take place if the vertex is visited. The objective is to find a set of routes such that the total traveling cost is minimized, exactly one vertex per cluster is visited, and all the capacity and time constraints are respected. This paper presents a set covering formulation for the GVRPTW which is used to provide a column generation based heuristic to solve it. The proposed solving method combines several components including a construction heuristic, a route optimization procedure, local search operators and the generation of negative reduced cost routes. Experimental results on benchmark instances show that the proposed algorithm is efficient and high-quality solutions for instances with up to 120 clusters are obtained within short computation times.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL