Problèmes de Tournées de Véhicules avec Synchronisation de Ressources

This dissertation focuses on vehicle routing problems, one of the major academic problems in logistics. We address NP-Hard problems that model some real world situations particularly those with different temporal constraints including time windows, visit synchronization and service balance.The aim of this research is to develop new algorithms for the considered problems, investigate their performance and compare them with the literature approaches. Two cases are carried out. The first case studies the Vehicle Routing Problem with Time Windows (VRPTW). We propose new lower bound methods for the number of vehicles. Then we present a Particle Swarm Optimization algorithm dealing with the Solomon objective. The second case studies the Vehicle Routing Problem with Time Windows and Synchronized Visits (VRPTWsyn). Both exact methods and heuristics are proposed and compared to the literature approaches.Cette thèse porte sur la résolution de problèmes de transport qui intègrent des contraintes temporelles considérant les fenêtres de temps, la synchronisation des visites et l’équilibrage des services. Ces problèmes trouvent plusieurs applications dans le monde réel.L’objectif de nos recherches est l’élaboration de nouvelles méthodes de résolution pour les problèmes considérés en examinant leur performance avec une étude comparative par rapport aux différentes approches de la littérature. Deux variantes sont traitées. Le premier cas étudie le Problème de Tournées de Véhicules avec Fenêtres de Temps (VRPTW). Nous proposons de nouveaux prétraitements et bornes inférieures pour déterminer le nombre de véhicules nécessaires en s’inspirant de travaux menés en ordonnancement (raisonnement énergétique) et d’autres problèmes combinatoires comme la clique maximum et les problèmes de bin-packing. Nous présentons également un algorithme d’optimisation par essaim particulaire qui traite de la minimisation du nombre de véhicules puis de celle du temps de trajet total. Le deuxième cas étudie le Problème de Tournées de Véhicules avec des Fenêtres de Temps et des Visites Synchronisées (VRPTWSyn). Nous proposons plusieurs méthodes basées sur des approches heuristiques et des formulations linéaires avec l’incorporation d’inégalités valides pour tenir compte de la contrainte de synchronisation

Méthodes exactes et approchées pour le problème de gestion de projet à contraintes de ressources

Le problème de gestion de projet à contraintes de ressources est un des problèmesles plus étudiés dans la littérature. Il consiste à planifier des activités soumises à desrelations de précédence, et nécessitant des ressources renouvelables. L objectif est deminimiser la durée du projet, soit le makespan. Nous étudions le problème de gestion deprojet à contraintes de ressources. Nous nous sommes intéressées à la résolution exactedu problème. Dans la première partie de la thèse, nous élaborons une série de bornesinférieures basées sur le raisonnement énergétique et des formulations mathématiques.Les résultats montrent que les bornes proposées surpassent ceux de la littérature. Dansla deuxième partie, nous proposons des procédures par séparation et évaluation utilisantles bornes inférieures dévelopées dans la première partie.Resource Constrained Project Scheduling Problem is one of the most studied schedulingproblems in the literature. It consists in scheduling activities, submitted to precedencerelationship, and requiring renewable resources to be processed. The objective isto minimize the project duration, i.e., the makespan. We study the Resource ConstrainedProject Scheduling Problem. We are interested on the exact resolution of the problem.In the first part of the thesis, we develop a series of lower bounds based on energeticreasoning and mathematical formulations. The computational results show that theproposed lower bounds outperform the ones of the literature. In the second part, wepropose Branch-and-Bound procedures using the lower bounds developed on the firstpart.TOURS-Bibl.électronique (372610011) / SudocSudocFranceF

Problèmes de tournées de véhicules et application industrielle pour la réduction de l'empreinte écologique

Dans cette thèse, nous nous sommes intéressés à la résolution approchée de problèmes de tournées de véhicules. Nous avons exploité des travaux menés sur les graphes d'intervalles et des propriétés de dominance relatives aux tournées saturées pour traiter les problèmes de tournées sélectives plus efficacement. Des approches basées sur un algorithme d'optimisation par essaim particulaire et un algorithme mémétique ont été proposées. Les métaheuristiques développées font appel à un ensemble de techniques particulièrement efficaces telles que le découpage optimal, les opérateurs de croisement génétiques ainsi que des méthodes de recherches locales. Nous nous sommes intéressés également aux problèmes de tournées classiques avec fenêtres de temps. Différents prétraitements ont été introduits pour obtenir des bornes inférieures sur le nombre de véhicules. Ces prétraitements s'inspirent de méthodes issues de modèles de graphes, de problème d'ordonnancement et de problèmes de bin packing avec conflits. Nous avons montré également l'utilité des méthodes développées dans un contexte industriel à travers la réalisation d'un portail de services mobilité.In this thesis, we focused on the development of heuristic approaches for solvingvehicle routing problems. We exploited researches conducted on interval graphsand dominance properties of saturated tours to deal more efficiently with selectivevehicle routing problems. An adaptation of a particle swarm optimization algorithmand a memetic algorithm is proposed. The metaheuristics that we developed arebased on effective techniques such as optimal split, genetic crossover operatorsand local searches. We are also interested in classical vehicle problems with timewindows. Various pre-processing methods are introduced to obtain lower boundson the number of vehicles. These methods are based on many approaches usinggraph models, scheduling problems and bin packing problems with conflicts. Wealso showed the effectiveness of the developed methods with an industrial applicationby implementing a portal of mobility services.COMPIEGNE-BU (601592101) / SudocSudocFranceF

Doctor of Philosophy

dissertationSolutions to Partial Di erential Equations (PDEs) are often computed by discretizing the domain into a collection of computational elements referred to as a mesh. This solution is an approximation with an error that decreases as the mesh spacing decreases. However, decreasing the mesh spacing also increases the computational requirements. Adaptive mesh re nement (AMR) attempts to reduce the error while limiting the increase in computational requirements by re ning the mesh locally in regions of the domain that have large error while maintaining a coarse mesh in other portions of the domain. This approach often provides a solution that is as accurate as that obtained from a much larger xed mesh simulation, thus saving on both computational time and memory. However, historically, these AMR operations often limit the overall scalability of the application. Adapting the mesh at runtime necessitates scalable regridding and load balancing algorithms. This dissertation analyzes the performance bottlenecks for a widely used regridding algorithm and presents two new algorithms which exhibit ideal scalability. In addition, a scalable space- lling curve generation algorithm for dynamic load balancing is also presented. The performance of these algorithms is analyzed by determining their theoretical complexity, deriving performance models, and comparing the observed performance to those performance models. The models are then used to predict performance on larger numbers of processors. This analysis demonstrates the necessity of these algorithms at larger numbers of processors. This dissertation also investigates methods to more accurately predict workloads based on measurements taken at runtime. While the methods used are not new, the application of these methods to the load balancing process is. These methods are shown to be highly accurate and able to predict the workload within 3% error. By improving the accuracy of these estimations, the load imbalance of the simulation can be reduced, thereby increasing the overall performance

Scheduling of tests on vehicle prototypes

In the automotive industry, a manufacturer must perform several hundreds of tests on prototypes of a vehicle before starting its mass production. These tests must be allocated to suitable prototypes and ordered to satisfy temporal constraints and various kinds of test dependencies. To reduce costs, the manufacturer is interested in using the minimum number of prototypes. We apply Constraint Programming (CP) and a hybrid approach to solve the scheduling problem. Our CP method can achieve good feasible solutions even for our largest instances within a reasonable time. In comparison with existing methods, we can improve the solutions for most of our instances and reduce the average number of required prototypes. The hybrid approach uses mixed integer linear programming (MILP) to solve the planning part and CP to find the complete schedule. Although the hybrid approach is not as robust as CP with respect to data characteristics and additional constraints, it can complement CP in finding a better lower bound

LIPIcs, Volume 274, ESA 2023, Complete Volume

LIPIcs, Volume 274, ESA 2023, Complete Volum

Proceedings of the International Workshop "Innovation Information Technologies: Theory and Practice": Dresden, Germany, September 06-10.2010

This International Workshop is a high quality seminar providing a forum for the exchange of scientific achievements between research communities of different universities and research institutes in the area of innovation information technologies. It is a continuation of the Russian-German Workshops that have been organized by the universities in Dresden, Karlsruhe and Ufa before. The workshop was arranged in 9 sessions covering the major topics: Modern Trends in Information Technology, Knowledge Based Systems and Semantic Modelling, Software Technology and High Performance Computing, Geo-Information Systems and Virtual Reality, System and Process Engineering, Process Control and Management and Corporate Information Systems

LOGIC AND CONSTRAINT PROGRAMMING FOR COMPUTATIONAL SUSTAINABILITY

Computational Sustainability is an interdisciplinary field that aims to develop computational and mathematical models and methods for decision making concerning the management and allocation of resources in order to help solve environmental problems. This thesis deals with a broad spectrum of such problems (energy efficiency, water management, limiting greenhouse gas emissions and fuel consumption) giving a contribution towards their solution by means of Logic Programming (LP) and Constraint Programming (CP), declarative paradigms from Artificial Intelligence of proven solidity. The problems described in this thesis were proposed by experts of the respective domains and tested on the real data instances they provided. The results are encouraging and show the aptness of the chosen methodologies and approaches. The overall aim of this work is twofold: both to address real world problems in order to achieve practical results and to get, from the application of LP and CP technologies to complex scenarios, feedback and directions useful for their improvement