Titre :

Vehicle Routing Problem with Fair Profits and Time Windows

Auteur(s) :

López Sánchez, Aitor [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Center for Intelligent Information Technologies and their Applications [CETINIA]
Lujak, Marin [Auteur]
Center for Intelligent Information Technologies and their Applications [CETINIA]
Semet, Frédéric [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Billhardt, Holger [Auteur]
Center for Intelligent Information Technologies and their Applications [CETINIA]

Titre de la manifestation scientifique :

IEEE Conference on Systems, Man, and Cybernetics

Organisateur(s) de la manifestation scientifique :

IEEE

Ville :

Honolulu

Pays :

Etats-Unis d'Amérique

Date de début de la manifestation scientifique :

2023-10-01

Mot(s)-clé(s) en anglais :

multi-agent system distributed computing column generation vehicle routing problem fairness profit sharing
multi-agent system
distributed computing
column generation
vehicle routing problem
fairness
profit sharing

Discipline(s) HAL :

Informatique [cs]/Recherche d'information [cs.IR]
Informatique [cs]/Système multi-agents [cs.MA]

Résumé en anglais : [en]

In crowdsourced delivery organizations, where individual vehicles with sharedcommon goals may have conflicting individual interests, the preference is for collaborationover competition, provided it is less costly. However, ...
Lire la suite >In crowdsourced delivery organizations, where individual vehicles with sharedcommon goals may have conflicting individual interests, the preference is for collaborationover competition, provided it is less costly. However, achieving a balancebetween the efficiency of individual vehicles and the overall fleet poses a challenge.This paper introduces a novel Vehicle Routing Problem with Fair Profits and TimeWindows (VRP-FPTW), which aims to meet customer demand and stringent timewindows while maximizing the profit of the worst-off vehicle in the fleet. We proposea centralized and distributed vehicle routing model for this problem, bothwith quality of solution guarantees. The distributed approach is tailored for multi-agentsystems relying on a coordination mechanism where each vehicle modeled asan individually rational agent finds its route autonomously in coordination with afleet coordinator agent, without sharing its private information. The objective ofa vehicle agent is to maximize its own profit while following the fleet’s norms andregulations based on shared values. Simulation experiments provide compellingevidence of the robustness and scalability of the proposed distributed approach,showcasing significant enhancements in both solution quality and computationalefficiency, particularly when dealing with larger vehicle fleets.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

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

Source :

Harvested from HAL