12 research outputs found

    A Branch-and-Cut Algorithm for the Capacitated Open Vehicle Routing Problem

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    In open vehicle routing problems, the vehicles are not required to return to the depot after completing service. In this paper, we present the first exact optimization algorithm for the open version of the well-known capacitated vehicle routing problem (CVRP). The algorithm is based on branch-and-cut. We show that, even though the open CVRP initially looks like a minor variation of the standard CVRP, the integer programming formulation and cutting planes need to be modified in subtle ways. Computational results are given for several standard test instances, which enables us for the first time to assess the quality of existing heuristic methods, and to compare the relative difficulty of open and closed versions of the same problem.Vehicle routing; branch-and-cut; separation

    Ride-matching and routing optimisation: Models and a large neighbourhood search heuristic

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    This paper considers a ridesharing problem on how to match riders to drivers and how to choose the best routes for vehicles. Unlike the others in the literature, we are concerned with the maximization of the average loading ratio of the entire system. Moreover, we develop a flow-dependent version of the model to characterize the impact of pick-up and drop-off congestion. In another extended model we take into account the riders’ individual evaluation on different transportation modes. Due to the large size of the resulting models, we develop a large neighbourhood search algorithm and demonstrate its efficiency

    IntĂ©gration de l’incertitude sur les tournĂ©es de vĂ©hicules et sur l’horaire de chargement dans le milieu forestier

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    RÉSUMÉ : Ce mĂ©moire de maĂźtrise traite d’une partie spĂ©cifique de la chaĂźne de valeur du secteur forestier canadien, soit le transport des billots de bois entre les sites forestiers et les usines de transformation. Cette Ă©tude traite, plus spĂ©cifiquement, de l’obtention des horaires de tournĂ©es de vĂ©hicules, selon plusieurs mĂ©thodologies combinant la gĂ©nĂ©ration de colonnes, l’utilisation de programmes linĂ©aires en nombres entiers (PLNE) ainsi que d’un simulateur. Le gĂ©nĂ©rateur de colonnes sert Ă  l’obtention d’un ensemble initial de tournĂ©es, tandis que les programmes linĂ©aires en nombres entiers servent Ă  obtenir un horaire final avec des valeurs entiĂšres, selon les diffĂ©rentes variables du problĂšme. Le simulateur a comme fonctionnalitĂ© la crĂ©ation d’imprĂ©vus dans la planification des camions de livraison, selon certains scĂ©narios. La nature de ces imprĂ©vus est dĂ©finie par deux catĂ©gories: la premiĂšre correspond Ă  des imprĂ©vus causĂ©s par des conditions routiĂšres difficiles, lors de perturbations mĂ©tĂ©orologiques. Ces situations de mauvais temps engendrent des dĂ©synchronisations sur la planification des tournĂ©es de vĂ©hicules au niveau des chemins empruntĂ©s par les camions forestiers. La deuxiĂšme catĂ©gorie d’imprĂ©vus produite par le simulateur met l’emphase sur la crĂ©ation d’achalandage aux usines de transformation ainsi qu’aux sites forestiers, causĂ©s par des camions d’autres compagnies externes Ɠuvrant dans le secteur du bois. L’objectif de cette recherche est d’analyser l’impact de la crĂ©ation d’imprĂ©vus sur les horaires de tournĂ©es de vĂ©hicules, soit la dĂ©synchronisation de la planification du transport routier via les outils Ă©numĂ©rĂ©s ci-haut. Trois mĂ©thodologies ont Ă©tĂ© utilisĂ©es dans cette analyse afin de tester la performance des planifications face aux Ă©vĂ©nements imprĂ©vus. La premiĂšre consiste Ă  gĂ©nĂ©rer l’horaire final des tournĂ©es des camions entre les sites forestiers et les usines de transformation, par l’entremise du gĂ©nĂ©rateur de colonnes et d’un PLNE, qui sont conjointement programmĂ©s dans un mĂȘme modĂšle en C++. Ensuite, le simulateur ajoute des dĂ©lais alĂ©atoirement, selon les deux types d’imprĂ©vus citĂ©s ci-haut, modifiant ainsi, dĂ©pendamment de la valeur des paramĂštres stochastiques, l’horaire final de tournĂ©es de vĂ©hicules. La seconde mĂ©thodologie consiste Ă  utiliser le gĂ©nĂ©rateur de colonnes afin d’obtenir un horaire initial, suivi immĂ©diatement de l’ajout d’imprĂ©vus par le simulateur, et ce avant l’utilisation du mĂȘme PLNE programmĂ© en C++. Ce dernier sera ensuite utilisĂ© afin d’obtenir un horaire basĂ© sur la moyenne des temps de passage des camions aux localisations et contenant des valeurs en nombres entiers. Puis, la troisiĂšme mĂ©thodologie consiste toujours Ă  utiliser, dans le mĂȘme ordre, le gĂ©nĂ©rateur de colonnes ainsi que le simulateur. Par contre, un PLNE programmĂ© dans le logiciel AIMMS servira de solveur, afin de dĂ©terminer l’horaire final des tournĂ©es de vĂ©hicules. De plus, plusieurs rĂ©alisations ont Ă©tĂ© exĂ©cutĂ©es par le simulateur, crĂ©ant ainsi des probabilitĂ©s de passage des camions, selon l’ajout alĂ©atoire de conditions routiĂšres difficiles. Le PLNE programmĂ© dans AIMMS utilise ces probabilitĂ©s de passage afin de dĂ©terminer un horaire de tournĂ©es de vĂ©hicules final avec des valeurs entiĂšres. Les imprĂ©vus crĂ©Ă©s par le simulateur ont comme objectif de reproduire certains scĂ©narios conçus pour reprĂ©senter, le plus fidĂšlement possible, la rĂ©alitĂ© observĂ©e sur le terrain. Afin de recrĂ©er des scĂ©narios rĂ©alistes Ă  propos du milieu forestier canadien, les valeurs des paramĂštres du simulateur ont Ă©tĂ© modifiĂ©es en consĂ©quence. Les paramĂštres du simulateur en question ont Ă©tĂ© calibrĂ©s selon des hypothĂšses basĂ©es sur des sources d’informations provenant de la compagnie FPInnovations ainsi que du MinistĂšre des Ressources Naturelles du QuĂ©bec. L’objectif de cette recherche est d’analyser les consĂ©quences de la gĂ©nĂ©ration d’imprĂ©vus dans l’horaire de tournĂ©es de vĂ©hicules, soit le nombre de retards total ainsi que le temps total de dĂ©lais sur l’ensemble de la flotte de camions. Le but est de comparer les trois mĂ©thodologies par l’entremise des dĂ©lais gĂ©nĂ©rĂ©s sur les horaires finaux des camions, impactant ainsi la livraison des billots de bois. Suite Ă  l’obtention des rĂ©sultats des trois mĂ©thodologies, la gĂ©nĂ©ration d’imprĂ©vus en lien avec des activitĂ©s externes n’a eu aucun impact significatif sur la planification des tournĂ©es de vĂ©hicules ainsi que sur la synchronisation de la machinerie, exceptĂ© pour la troisiĂšme mĂ©thodologie, oĂč de l’achalandage aux usines de transformation est Ă  priori prĂ©sent dans les horaires finaux de tournĂ©es de vĂ©hicules. Par contre, la crĂ©ation de conditions routiĂšres difficiles a engendrĂ© des dĂ©lais de l’ordre de plusieurs heures par pĂ©riode de simulation et par camion. Sommairement, au niveau des trois mĂ©thodologies Ă©tudiĂ©es dans ce projet de recherche, la deuxiĂšme approche, qui consiste Ă  ajouter des dĂ©lais dans la planification avant la gĂ©nĂ©ration des horaires finaux avec le PLNE en C++, a dĂ©montrĂ© qu’elle rĂ©agit mieux face aux imprĂ©vus. La premiĂšre approche dĂ©montre des rĂ©sultats oĂč les dĂ©lais engendrĂ©s par les conditions mĂ©tĂ©orologiques difficiles sont plus considĂ©rables. La troisiĂšme approche dĂ©montre des rĂ©sultats similaires Ă  la seconde approche, mais aprĂšs la gĂ©nĂ©ration d’imprĂ©vus, la moyenne de dĂ©lais pĂ©riodiques par camion est lĂ©gĂšrement plus Ă©levĂ©e que ceux de la seconde approche.----------ABSTRACT : The context of this study is concerning one part of the forest sector supply chain: the log-truck planning. This research project is studying different methodologies to generate log-truck schedules, by using a column generation program, two different mixed integer programs and a simulator. The column generation program and the mixed integer programs are used to create feasible schedules for the whole truck fleet, while respecting the different constraints of the log-truck scheduling problem. The simulator is used to generate two different types of delays: the first type is concerning the generation of difficult road conditions. The second type of delay is about the creation of traffic at mills and forest sites, caused by trucks from other companies. These two types of delays generate disturbance on the initial log-truck schedule planning. In order to analyze these disturbances on the log-truck network, three methodologies have been developed to generate delays in the log-truck schedule planning. The first methodology relates the use of the column generation program, follow by a mixed integer program in C++ to generate feasible schedules with integer values. After, the simulator is used to insert delays in the schedules. The second methodology relates also the use of the column generation program, but followed this time by the simulator, that inserts delays before using the mixed integer program (MIP) in C++ and having an integer schedule. And the third methodology is also using the column generation program, follow by the simulator. However, instead of using the MIP in C++, a new MIP in the software AIMMS is used to find an integer solution. The objective here is to analyze the different results of each methodology, that is to say the total amount of delays for each type, the total delay time and the disturbance on the initial schedules. The analysis of these three methodologies is made on several scenarios that reflect the reality observed in the forest sector as much as possible. The results of this research show that the generation of external jobs at mills and forests doesn’t have a significant impact on the initial log-truck planning, only on the third methodology, where there’s already some congestion at locations in the schedules. But, the generation of difficult road conditions by the simulator affects significantly the round trip schedules, with a few hours of delays per truck in their activities, regardless the approach. If we compare the three methodologies, the second one shows better results for the total average time delays per truck, with a smaller number of delays in the truck schedules, but this model needs more round trips to satisfy the demand

    Multistars, partial multistars and the capacitated vehicle routing problem

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    In an unpublished paper, Araque, Hall and Magnanti considered polyhedra associated with the Capacitated Vehicle Routing Problem (CVRP) in the special case of unit demands. Among the valid and facet-inducing inequalities presented in that paper were the so-called multistar and partial multistar inequalities, each of which came in several versions. Some related inequalities for the case of general demands have appeared subsequently and the result is a rather bewildering array of apparently different classes of inequalities. The main goal of the present paper is to present two relatively simple procedures that can be used to show the validity of all known (and some new) multistar and partial multistar inequalities, in both the unit and general demand cases. The procedures provide a unifying explanation of the inequalities and, perhaps more importantly, ideas that can be exploited in a cutting plane algorithm for the CVRP. Computational results show that the new inequalities can be useful as cutting planes for certain CVRP instances

    The capacitated minimum spanning tree problem

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    In this thesis we focus on the Capacitated Minimum Spanning Tree (CMST), an extension of the minimum spanning tree (MST) which considers a central or root vertex which receives and sends commodities (information, goods, etc) to a group of terminals. Such commodities flow through links which have capacities that limit the total flow they can accommodate. These capacity constraints over the links result of interest because in many applications the capacity limits are inherent. We find the applications of the CMST in the same areas as the applications of the MST; telecommunications network design, facility location planning, and vehicle routing. The CMST arises in telecommunications networks design when the presence of a central server is compulsory and the flow of information is limited by the capacity of either the server or the connection lines. Its study also results specially interesting in the context of the vehicle routing problem, due to the utility that spanning trees can have in constructive methods. By the simple fact of adding capacity constraints to the MST problem we move from a polynomially solvable problem to a non-polynomial one. In the first chapter we describe and define the problem, introduce some notation, and present a review of the existing literature. In such review we include formulations and exact methods as well as the most relevant heuristic approaches. In the second chapter two basic formulations and the most used valid inequalities are presented. In the third chapter we present two new formulations for the CMST which are based on the identification of subroots (vertices directly connected to the root). One way of characterizing CMST solutions is by identifying the subroots and the vertices assigned to them. Both formulations use binary decision variables y to identify the subroots. Additional decision variables x are used to represent the elements (arcs) of the tree. In the second formulation the set of x variables is extended to indicate the depth of the arcs in the tree. For each formulation we present families of valid inequalities and address the separation problem in each case. Also a solution algorithm is proposed. In the fourth chapter we present a biased random-key genetic algorithm (BRKGA) for the CMST. BRKGA is a population-based metaheuristic, that has been used for combinatorial optimization. Decoders, solution representation and exploring strategies are presented and discussed. A final algorithm to obtain upper bounds for the CMST is proposed. Numerical results for the BRKGA and two cutting plane algorithms based on the new formulations are presented in the fifth chapter . The above mentioned results are discussed and analyzed in this same chapter. The conclusion of this thesis are presented in the last chapter, in which we include the opportunity areas suitable for future research.En esta tesis nos enfocamos en el problema del Árbol de ExpansiĂłn Capacitado de Coste MĂ­nimo (CMST, por sus siglas en inglĂ©s), que es una extensiĂłn del problema del ĂĄrbol de expansiĂłn de coste mĂ­nimo (MST, por sus siglas en inglĂ©s). El CMST considera un vĂ©rtice raĂ­z que funciona como servidor central y que envĂ­a y recibe bienes (informaciĂłn, objetos, etc) a un conjunto de vĂ©rtices llamados terminales. Los bienes solo pueden fluir entre el servidor y las terminales a travĂ©s de enlaces cuya capacidad es limitada. Dichas restricciones sobre los enlaces dan relevancia al problema, ya que existen muchas aplicaciones en que las restricciones de capacidad son de vital importancia. Dentro de las ĂĄreas de aplicaciĂłn del CMST mĂĄs importantes se encuentran las relacionadas con el diseño de redes de telecomunicaciĂłn, el diseño de rutas de vehĂ­culos y problemas de localizaciĂłn. Dentro del diseño de redes de telecomunicaciĂłn, el CMST estĂĄ presente cuando se considera un servidor central, cuya capacidad de transmisiĂłn y envĂ­o estĂĄ limitada por las caracterĂ­sticas de los puertos del servidor o de las lĂ­neas de transmisiĂłn. Dentro del diseño de rutas de vehĂ­culos el CMST resulta relevante debido a la influencia que pueden tener los ĂĄrboles en el proceso de construcciĂłn de soluciones. Por el simple de añadir las restricciones de capacidad, el problema pasa de resolverse de manera exacta en tiempo polinomial usando un algoritmo voraz, a un problema que es muy difĂ­cil de resolver de manera exacta. En el primer capĂ­tulo se describe y define el problema, se introduce notaciĂłn y se presenta una revisiĂłn bibliogrĂĄfica de la literatura existente. En dicha revisiĂłn bibliogrĂĄfica se incluyen formulaciones, mĂ©todos exactos y los mĂ©todos heurĂ­sticos utilizados mĂĄs importantes. En el siguiente capĂ­tulo se muestran dos formulaciones binarias existentes, asĂ­ como las desigualdades vĂĄlidas mĂĄs usadas para resolver el CMST. Para cada una de las formulaciones propuestas, se describe un algoritmo de planos de corte. Dos nuevas formulaciones para el CMST se presentan en el tercer capĂ­tulo. Dichas formulaciones estĂĄs basadas en la identificaciĂłn de un tipo de vĂ©rtices especiales llamados subraĂ­ces. Los subraĂ­ces son aquellos vĂ©rtices que se encuentran directamente conectados al raĂ­z. Un forma de caracterizar las soluciones del CMST es a travĂ©s de identificar los nodos subraĂ­ces y los nodos dependientes a ellos. Ambas formulaciones utilizan variables para identificar los subraices y variables adicionales para identificar los arcos que forman parte del ĂĄrbol. Adicionalmente, las variables en la segunda formulaciĂłn ayudan a identificar la profundidad con respecto al raĂ­z a la que se encuentran dichos arcos. Para cada formulaciĂłn se presentan desigualdades vĂĄlidas y se plantean procedimientos para resolver el problema de su separaciĂłn. En el cuarto capĂ­tulo se presenta un algoritmo genĂ©tico llamado BRKGA para resolver el CMST. El BRKGA estĂĄ basado en el uso de poblaciones generadas por secuencias de nĂșmeros aleatorios, que posteriormente evolucionan. Diferentes decodificadores, un mĂ©todo de bĂșsqueda local, espacios de bĂșsqueda y estrategias de exploraciĂłn son presentados y analizados. El capĂ­tulo termina presentando un algoritmo final que permite la obtenciĂłn de cotas superiores para el CMST. Los resultados computacionales para el BRKGA y los dos algoritmos de planos de corte basados en las formulaciones propuestas se muestran en el quinto capĂ­tulo. Dichos resultados son analizados y discutidos en dicho capĂ­tulo. La tesis termina presentando las conclusiones derivadas del desarrollo del trabajo de investigaciĂłn, asĂ­ como las ĂĄreas de oportunidad sobre las que es posible realizar futuras investigaciones

    A Branch-and-Cut based Pricer for the Capacitated Vehicle Routing Problem

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    openIl Capacitated Vehicle Routing Problem, abbreviato come CVRP, Ăš un problema di ottimizzazione combinatoria d'instradamento nel quale, un insieme geograficamente sparso di clienti con richieste note deve essere servito da una flotta di veicoli stazionati in una struttura centrale. Negli ultimi due decenni, tecniche di Column generation incorporate all'interno di frameworks branch-price-and-cut sono state infatti l'approccio stato dell'arte dominante per la costruzione di algoritmi esatti per il CVRP. Il pricer, un componente critico nella column generation, deve risolvere il Pricing Problem (PP) che richiede la risoluzione di un Elementary Shortest Path Problem with Resource Constraints (ESPPRC) in una rete di costo ridotto. Pochi sforzi scientifici sono stati dedicati allo studio di approcci branch-and-cut per affrontare il PP. L'ESPPRC Ăš stato tradizionalmente rilassato e risolto attraverso algoritmi di programmazione dinamica. Questo approccio, tuttavia, ha due principali svantaggi. Per cominciare, peggiora i dual bounds ottenuti. Inoltre, il tempo di esecuzione diminuisce all'aumentare della lunghezza dei percorsi generati. Per valutare la performance dei loro contributi, la comunitĂ  di ricerca operativa ha tradizionalmente utilizzato una serie d'istanze di test storiche e artificiali. Tuttavia, queste istanze di benchmark non catturano le caratteristiche chiave dei moderni problemi di distribuzione del mondo reale, che sono tipicamente caratterizzati da lunghi percorsi. In questa tesi sviluppiamo uno schema basato su un approccio branch-and-cut per risolvere il pricing problem. Studiamo il comportamento e l'efficacia della nostra implementazione nel produrre percorsi piĂč lunghi comparandola con soluzioni all'avanguardia basate su programmazione dinamica. I nostri risultati suggeriscono che gli approcci branch-and-cut possono supplementare il tradizionale algoritmo di etichettatura, indicando che ulteriore ricerca in quest'area possa portare benefici ai risolutori CVRP.The Capacitated Vehicle Routing Problem, CVRP for short, is a combinatorial optimization routing problem in which, a geographically dispersed set of customers with known demands must be served by a fleet of vehicles stationed at a central facility. Column generation techniques embedded within branch-price-and-cut frameworks have been the de facto state-of-the-art dominant approach for building exact algorithms for the CVRP over the last two decades. The pricer, a critical component in column generation, must solve the Pricing Problem (PP), which asks for an Elementary Shortest Path Problem with Resource Constraints (ESPPRC) in a reduced-cost network. Little scientific efforts have been dedicated to studying branch-and-cut based approaches for tackling the PP. The ESPPRC has been traditionally relaxed and solved through dynamic programming algorithms. This approach, however, has two major drawbacks. For starters, it worsens the obtained dual bounds. Furthermore, the running time degrades as the length of the generated routes increases. To evaluate the performance of their contributions, the operations research community has traditionally used a set of historical and artificial test instances. However, these benchmark instances do not capture the key characteristics of modern real-world distribution problems, which are usually characterized by longer routes. In this thesis, we develop a scheme based on a branch-and-cut approach for solving the pricing problem. We study the behavior and effectiveness of our implementation in producing longer routes by comparing it with state-of-the-art solutions based on dynamic programming. Our results suggest that branch-and-cut approaches may supplement the traditional labeling algorithm, indicating that further research in this area may bring benefits to CVRP solvers

    Transportation Optimization in Tactical and Operational Wood Procurement Planning

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    RÉSUMÉ : L'Ă©conomie canadienne est dĂ©pendante du secteur forestier. Cependant, depuis quelques annĂ©es, ce secteur fait face Ă  de nouveaux dĂ©fis, tels que la rĂ©cession mondiale, un dollar canadien plus fort et une baisse significative de la demande de papier journal. Dans ce nouveau contexte, une planification plus efficace de la chaĂźne d'approvisionnement est devenue un Ă©lĂ©ment essentiel pour assurer le succĂšs et la pĂ©rennitĂ© du secteur. Les coĂ»ts de transport reprĂ©sentent une dĂ©pense importante pour les entreprises forestiĂšres. Ceci est dĂ» aux grands volumes de produits qui doivent ĂȘtre transportĂ©s sur de grandes distances, en particulier dans le contexte gĂ©ographique d'un grand pays comme le Canada. MĂȘme si les problĂšmes de tournĂ©e de vĂ©hicules sont bien couverts dans la littĂ©rature, le secteur forestier a beaucoup de caractĂ©ristiques uniques qui nĂ©cessitent de nouvelles formulations des problĂšmes et des algorithmes de rĂ©solution. À titre d’exemple, les volumes Ă  transporter sont importants comparĂ©s Ă  d’autres secteurs et il existe aussi des contraintes de synchronisation Ă  prendre en compte pour planifier l'Ă©quipement qui effectue le chargement et le dĂ©chargement des vĂ©hicules. Cette thĂšse traite des problĂšmes de planification de la chaĂźne logistique d'approvisionnement en bois: rĂ©colter diverses variĂ©tĂ©s de bois en forĂȘt et les transporter par camion aux usines et aux zones de stockage intermĂ©diaire en respectant la demande pour les diffĂ©rents produits forestiers. Elle propose trois nouvelles formulations de ces problĂšmes. Ces problĂšmes sont diffĂ©rents les uns des autres dans des aspects tel que l'horizon de planification et des contraintes industrielles variĂ©es. Une autre contribution de cette thĂšse sont les mĂ©thodologies dĂ©veloppĂ©es pour rĂ©soudre ces problĂšmes dans le but d’obtenir des calendriers d’approvisionnement applicables par l’industrie et qui minimisent les coĂ»ts de transport. Cette minimisation est le rĂ©sultat d’allocations plus intelligentes des points d'approvisionnement aux points de demande, d’une tournĂ©e de vĂ©hicules qui minimise la distance parcourue Ă  vide et de dĂ©cisions d'ordonnancement de vĂ©hicules qui minimisent les files d’attentes des camions pour le chargement et le dĂ©chargement. Dans le chapitre 3 on considĂšre un modĂšle de planification tactique de la rĂ©colte. Dans ce problĂšme, on dĂ©termine la sĂ©quence de rĂ©colte pour un ensemble de sites forestiers, et on attribue des Ă©quipes de rĂ©colte Ă  ces sites. La formulation en programme linĂ©aire en nombres entiers (PLNE) de ce problĂšme gĂšre les dĂ©cisions d'inventaire et alloue les flux de bois Ă  des entrepreneurs de transport routier sur un horizon de planification annuel. La nouveautĂ© de notre approche est d'intĂ©grer les dĂ©cisions de tournĂ©e des vĂ©hicules dans la PLNE. Cette mĂ©thode profite de la flexibilitĂ© du plan de rĂ©colte pour satisfaire les horaires des conducteurs dans le but de conserver une flotte constante de conducteurs permanents et Ă©galement pour minimiser les coĂ»ts de transport. Une heuristique de gĂ©nĂ©ration de colonnes est crĂ©Ă©e pour rĂ©soudre ce problĂšme avec un sous-problĂšme qui consiste en un problĂšme du plus court chemin avec capacitĂ©s (PCCC) avec une solution qui reprĂ©sente une tournĂ©e de vĂ©hicule. Dans le chapitre 4, on suppose que le plan de rĂ©colte est fixĂ© et on doit dĂ©terminer les allocations et les inventaires du modĂšle tactique prĂ©cĂ©dent, avec aussi des dĂ©cisions de tournĂ©e et d'ordonnancement de vĂ©hicules. On synchronise les vĂ©hicules avec les chargeuses dans les forĂȘts et dans les usines. Les contraintes de synchronisation rendent le problĂšme plus difficile. L’objectif est de dĂ©terminer la taille de la flotte de vĂ©hicules dans un modĂšle tactique et de satisfaire la demande des usines avec un coĂ»t minimum. Le PLNE est rĂ©solu par une heuristique de gĂ©nĂ©ration de colonnes. Le sous-problĂšme consiste en un PCCC avec une solution qui reprĂ©sente une tournĂ©e et un horaire quotidien d'un vĂ©hicule. Dans le chapitre 5, on considĂšre un PLNE du problĂšme similaire Ă  celui Ă©tudiĂ© dans le chapitre 4, mais dans un contexte plus opĂ©rationnel: un horizon de planification d'un mois. Contrairement aux horaires quotidiens de vĂ©hicules du problĂšme prĂ©cĂ©dent, on doit planifier les conducteurs par semaine pour gĂ©rer les situations dans lesquelles le dĂ©chargement d’un camion s’effectue le lendemain de la journĂ©e oĂč le chargement a eu lieu. Cette situation se prĂ©sente quand les conducteurs travaillent la nuit ou quand ils travaillent aprĂšs les heures de fermeture de l'usine et doivent dĂ©charger leur camion au dĂ©but de la journĂ©e suivante. Ceci permet aussi une gestion plus directe des exigences des horaires hebdomadaires. Les contraintes de synchronisation entre les vĂ©hicules et les chargeuses qui sont prĂ©sentes dans le PLNE permettent de crĂ©er un horaire pour chaque opĂ©rateur de chargeuse. Les coĂ»ts de transport sont alors minimisĂ©s. On rĂ©sout le problĂšme Ă  l’aide d’une heuristique de gĂ©nĂ©ration de colonnes. Le sous-problĂšme consiste en un PCCC avec une solution qui reprĂ©sente une tournĂ©e et un horaire hebdomadaire d’un vĂ©hicule.----------ABSTRACT : The Canadian economy is heavily dependent on the forestry industry; however in recent years, this industry has been adapting to new challenges including a worldwide economic downturn, a strengthening Canadian dollar relative to key competing nations, and a significant decline in newsprint demand. Therefore efficiency in supply chain planning is key for the industry to succeed in the future. Transportation costs in particular represent a significant expense to forestry companies. This is due to large volumes of product that must be transported over very large distances, especially in the geographic context of a country the size of Canada. While the field of vehicle routing problems has been heavily studied and applied to many industries for decades, the forestry industry has many unique attributes that necessitate new problem formulations and solution methodologies. These include, but are not limited to, very large (significantly higher than vehicle capacity) volumes to be transported and synchronization constraints to schedule the equipment that load and unload the vehicles. This thesis is set in the wood procurement supply chain of harvesting various assortments of wood in the forest, transporting by truck to mills and intermediate storage locations, while meeting mill demands of the multiple harvested products, and contributes three new problem formulations. These problems differ with respect to planning horizon and varied industrial constraints. Another contribution is the methodologies developed to resolve these problems to yield industrially applicable schedules that minimize vehicle costs: from smarter allocations of supply points to demand points, vehicle routing decisions that optimize the occurrence of backhaul savings, and vehicle scheduling decisions that minimize queues of trucks waiting for loading and unloading equipment. In Chapter 3, we consider a tactical harvest planning model. In this problem we determine the sequence of the harvest of various forest sites, and assign harvest teams to these sites. The MILP formulation of this problem makes inventory decisions and allocates wood flow to trucking contractors over the annual planning horizon, subject to demand constraints and trucking capacities. The novel aspect of our approach is to incorporate vehicle routing decisions into our MILP formulation. This takes advantage of the relatively higher flexibility of the harvest plan to ensure driver shifts of desired characteristics, which is important to retain a permanent driver fleet, and also prioritize the creation of backhaul opportunities in the schedule. A branch-and-price heuristic is developed to resolve this problem, with the subproblem being a vehicle routing problem that represents a geographical shift for a vehicle. In Chapter 4, we assume the harvest plan to be an input, and integrate the allocation and inventory variables of the previous tactical model with vehicle routing and scheduling decisions, synchronizing the vehicles with loaders in the forests and at the mills. The synchronization constraints make a considerably more difficult problem. We use this as a tactical planning model, with no specific driver constraints but a goal of determining vehicle fleet size to maximize their utilization. The objective is to meet mill demands over the planning horizon while minimizing transportation and inventory costs, subject to capacity, wood freshness, fleet balancing, and other industrial constraints. The MILP formulation of the problem is resolved via a column generation algorithm, with the subproblem being a daily vehicle routing and scheduling problem. In Chapter 5, we consider a similar problem formulation to that studied in Chapter 4, but set in a more operational context over a planning horizon of approximately one month. Unlike the daily vehicle schedules of the previous problem, we must schedule drivers by week to manage situations of picking up a load on one day and delivering on another day, which is necessary when drivers work overnight shifts or when they work later than mill closing hours and must unload their truck on the next day's shift. This also allows for more direct management of weekly schedule requirements. Loader synchronization constraints are present in the model which derives a schedule for each loader operator. Given mill demands, transportation costs are then minimized. We resolve the problem via a branch-and-price heuristic, with a subproblem of a weekly vehicle routing and scheduling problem. We also measure the benefits of applying interior point stabilization to the resource synchronization constraints in order to improve the column generation, a new application of the technique
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