A VNS-based Heuristic for Solving the Vehicle Routing Problem with Time Windows and Vehicle Preventive Maintenance Constraints

AbstractWe address a vehicle routing problem with time windows (VRPTW) that also contains vehicle with preventive maintenance constraints (VRPTW-PM) and propose a MIP mathematical formulation as well as a general variable neighborhood search metaheuristic (VNS) to solve with large instance the problematic situation. First we create a initial solution using Solomon heuristic then we minimize the number of used routes, and then the total travelled distance by all vehicles is minimized. Computational results show the efficiency of the proposed approach

Distributed genetic algorithm for disaster relief planning

The problem studied in this paper is the management of vehicle routing in case of emergency. It is decomposed into two parts. The first one deals with the emergency planning in the event of receiving a set of requests for help after a major disaster such as in the case of an earthquake, hurricane, flood, etc. The second part concerns the treatment of contingency as the arrival of a new request or the appearance of a disturbance such as breakdowns of vehicles, the malfunction of roads, availability of airports, etc. To solve this problem we proposed a multi-agents approach using a guided genetic algorithm for scheduling vehicle routing and local search for the management of contingencies. The main objectif of our approach was to maximizing the number of saved people and minimizing the costs of the rescue operation. This approach was tested with the modified Solomon benchmarks and gave good results

Système Interactif d'Aide au Déplacement Multimodal (SIADM)

The objective of this work is the realization of a system allowing to assist the travellers, and to facilitate their movement in normal and degraded functioning of the transport network. This system aims to minimize the waiting time of the travellers, in degraded mode, at exchanges stations and to assure them, as well as possible, the continuity of their journey in the multimodal transport networks. So it improves the quality of the service returned to the travellers in order to inform them. A first part of the work in this thesis concerns conception, development and validation of our approach which allows giving optimal or almost optimal solutions for a normal and disrupted transport system. This approach uses a multi-objective method of search for optimal route which leans on a hybridization between a modified Dijkstra algorithm and a genetic algorithm. The modified Dijkstra algorithm gives us a set as solutions serving of initial population for the genetic algorithm.The modelling of the transport system is represented by multi-zones architecture. This architecture shows us the distributed aspect of the system, and the interactions and the relations which can take place among various zones. We present in this work a Multi-agent system of Help to the Movement. These agents use the module of optimization developed in the first part. Our work is realized within the framework of the "VIATIC-MOBILITE" project, which is the project 6 of the I-Trans Competitiveness cluster.L'objectif de notre travail est la réalisation d'un système interactif d'aide aux déplacements, en mode normal, et en mode dégradé de fonctionnement du réseau de transport en commun. Ce système vise par ailleurs à minimiser le temps d'attente des voyageurs, en mode dégradé, dans les pôles d'échanges et à leur assurer, dans la mesure du possible, la continuité des déplacements dans les réseaux multimodaux. Il s'agit donc d'améliorer la qualité du service rendu aux voyageurs et les maintenir informés. Une grande partie du travail de cette thèse concerne la conception, le développement et la validation des approches qui permettent de donner des solutions optimales ou quasi optimales, pour un réseau de transport normal et perturbé. Ces approches utilisent une méthode multicritère de recherche d'itinéraire qui s'appuie sur une hybridation entre un algorithme de Dijkstra modifié et un algorithme génétique, pour générer une population de chemins minimums . L'algorithme de Dijkstra modifié nous donne un ensemble de solutions servant de population initiale pour l'algorithme génétique.La modélisation du réseau de transport est représentée par une architecture multi-zones . Cette architecture nous montre l'aspect distribué du système, les interactions et les relations qui peuvent avoir lieu entre les différenttes zones. Nous présentons dans ce travail un Système Multi-Agent d'Aide au Déplacement, SMAAD. Les agents de ce système utilisent le module d'optimisation développé dans la première partie. Notre travail est réalisé dans le cadre du projet « VIATIC-MOBILITE », qui est le projet 6 du pôle de compétitivité I-Trans

A contribution on the modeling and resolution of multi-objective Dial a Ride problem

International audienceThe paper describes a system for the solution of Dial a Ride Problem (DRP). Dial a Ride Problem (DRP) is to take over the passenger from a place of departure to a place of arrival. It is characterized by a set of transport demands and a number of vehicles available. The ultimate aim is to offer an alternative to displacement optimized individually and collectively. The DRP is classified as NP-hard problem which is why most research has been concentrated on the use of approximate methods to solve it. Indeed, it is a multi-criteria problem, the proposed solution of which aims to reduce both route duration, and cost in response to a certain quality of service provided. In this work, we offer our contribution to the study and solving the DRP in the application using the simulated annealing algorithm. Tests show competitive results on (Cordeau and Laporte, 2003) benchmark datasets while improving processing times

Modélisation d'un Système Multi-Agent pour la résolution d'un Problème de Tournées de Véhicule dans une situation d'urgence

International audienceCe papier propose une approche Multi-Agents pour la résolution d'un Problème de Tournées de Véhicules dans une situation d'urgence. Le contexte de ce problème est de planifier un ensemble de tournées pour servir un ensemble hétérogène de demandes en prévoyant des imprévus comme l'arrivée d'une nouvelle demande ou/et l'apparition d'une perturbation. Dans ce papier, nous nous intéressons surtout à la modélisation du système Multi- Agents. Notre SMA emploie trois classes d'agents à savoir l'agent Superviseur, l'agent Interface et l'agent Véhicule. Pour modéliser notre SMA nous avons utilisé la méthodologie O-MaSE

A Hybrid Method for Assigning Containers to AGVs in the Dynamic Environment of Container Terminals

International audienceThe handling operations performed in ports require the use of equipment operating in a dynamic environment. Some tasks may not be fully carried out due to equipment failure or power breakdown that may occur particularly with the automated guided vehicles (AGV). The unavailability of equipment such as AGV has important consequences in terms of respecting the deadlines of different operations that a port should perform, such as the loading and unloading operations of ships. This situation can aggravate if there are also traffic problems in the port with some inaccessible network nodes. A part of the equipment will be blocked or the operations will take longer than expected if they don`t take the optimal path to connect the loading/unloading points and storage areas. These reasons confirm the usefulness of establishing a robust system able to resolve the problem of assigning containers in the static and dynamic environments. In a previous work, we developed a system for assigning containers in a static environment. In order to improve this method, we devote this paper to the study of the robustness of our system to the dynamic environment of the port. The numerical tests included in this paper show an adequate performance of our method for this particular dynamic environment

A Hybrid Method for Assigning Containers to AGVs in the Dynamic Environment of Container Terminals

International audienceThe handling operations performed in ports require the use of equipment operating in a dynamic environment. Some tasks may not be fully carried out due to equipment failure or power breakdown that may occur particularly with the automated guided vehicles (AGV). The unavailability of equipment such as AGV has important consequences in terms of respecting the deadlines of different operations that a port should perform, such as the loading and unloading operations of ships. This situation can aggravate if there are also traffic problems in the port with some inaccessible network nodes. A part of the equipment will be blocked or the operations will take longer than expected if they don`t take the optimal path to connect the loading/unloading points and storage areas. These reasons confirm the usefulness of establishing a robust system able to resolve the problem of assigning containers in the static and dynamic environments. In a previous work, we developed a system for assigning containers in a static environment. In order to improve this method, we devote this paper to the study of the robustness of our system to the dynamic environment of the port. The numerical tests included in this paper show an adequate performance of our method for this particular dynamic environment

Optimization Problem of Assignment Containers to AIVs in a Container Terminal

International audienc

Optimization Problem of Assignment Containers to AIVs in a Container Terminal

International audienc

A hybrid genetic algorithm to solve the optimization problem of assignment containers to AIVs in a container terminal

International audienc