We consider the daily transportation problem in forestry which arises when transporting logs from forest sites to customers such as sawmills and pulp and paper mills. Each customer requires a specific amount of a certain assortment, and the deliveries to the customers can be made within time intervals, known as time windows. Further, there are a number of supply points, each with a certain assortment, and a number of vehicles of a given capacity, to be used for transport. The log truck scheduling problem consists of finding a set of minimal costs routes, one for each vehicle, such that the customers’ demands are satisfied without exceeding the supplies available at the supplies. Each route has to satisfy a number of constraints concerning time windows, truck capacity, timetable of the driver, lunch breaks, et cetera. The model used to describe the log truck scheduling problem is based on the route concept, and each variable, or column, represents one feasible route. Since the number of feasible routes is huge, we work only with restricted versions of this problem, which are similar to restricted master problems in a Dantzig-Wolfe decomposition scheme. We use three solution methods based on the column generation principle, together with a pool strategy which allows us to deal with the feasible routes outside the restricted master problem. The three methods proposed have a common structure; they use branch-andprice together with a column generator, followed by branch-and-bound. The column generators in the three methods differ. In the first method, the subproblem is based on a cluster-first-route-second strategy. The column generator in the second method involves solving a constrained shortest path problem, and finally, the third method builds on a repeated generation of clusters and routes. The three methods are tested on real cases from Swedish forestry companies, and the third method has been adapted to a computerised system that utilises the Swedish national road data base, for computing travelling distances. The results obtained show that the optimisation methods succeed in finding significantly better solutions than those obtained by manual planning, and in a reasonable computing time.

This dissertation details an algorithm to solve the Intratheater Airlift Operations Problem (IAOP) using advanced tabu search. A solution to the IAOP determines the routes and assignment of customer requests to a fleet of aircraft over a given time horizon. This problem and other variants comprise an ongoing challenge for United States Air Force (USAF) planners who manage detailed logistics throughout many theaters of operations. Attributes of the IAOP include cargo time windows, multiple cargo types, multiple vehicle cargo bay configurations, vehicle capacity, route duration limits, and port capacities. The IAOP multi-criteria objective embraces several components with the primary goal of satisfying as much of the demand as possible while minimizing cost. The algorithm is extended to allow split load deliveries of customer requests, allowing a shipment to be split into two or more sub-loads which are delivered separately to the customer. The split load relaxation, while significantly increasing the complexity of the problem, allows for possible improvement in the solution. The necessary changes to the model and algorithm are detailed, providing a foundation to extend any local search algorithm solving a vehicle routing problem to allow split loading. Results allowing split loading are presented and compared with results without split loading. The algorithm is also extended to include a rolling time horizon. Starting from a solution found at a previous time step, the algorithm is limited on how the solution can be modified. This reflects the reality of operations in which near-term plans are locked as they approach and enter execution while longer-term plans are continually updated as new information arrives. / text

Résumé indisponible. / The VIPAFLEET project aims at developing a framework to manage a fleet of IndividualPublic Autonomous Vehicles (VIPA). We consider a fleet of cars distributed at specifiedstations in an industrial area to supply internal transportation, where the cars can beused in different modes of circulation (tram mode, elevator mode, taxi mode). The goalis to develop and implement suitable algorithms for each mode in order to satisfy all therequests either under an economic point aspect or under a quality of service aspect, thisby varying the studied objective functions.We model the underlying online transportation system as a discrete event basedsystem and propose a corresponding fleet management framework, to handle modes,demands and commands. We consider three modes of circulation, tram, elevator andtaxi mode. We propose for each mode appropriate online algorithms and evaluate theirperformance, both in terms of competitive analysis and practical behavior by computationalresults. We treat in this work, the pickup and delivery problem related to theTram mode and the Elevator mode the pickup and delivery problem with time windowsrelated to the taxi mode by means of flows in time-expanded networks.

In this paper we consider a rich vehicle routing problem where transportation requests are characterised by multiple pickup and delivery locations. The problem is a combined load acceptance and generalised vehicle routing problem incorporating a diversity of practical complexities. Among those are time window restrictions, a heterogeneous vehicle fleet with different travel times, travel costs and capacity, multi-dimensional capacity constraints, order/vehicle compatibility constraints, and different start and end locations for vehicles. We propose iterative improvement approaches based on Large Neighborhood Search and a relatedness measure for transportation requests with multiple pickup and delivery locations. Our algorithms are characterised by very fast response times and thus, can be used within dynamic routing systems where input data can change at any time.

Le transport de matériaux pour la réalisation d’infrastructures routières et le terrassement représente, en 2013, plus de la moitié de l’activité du secteur des travaux publics. Les méthodes d’optimisation de tournées de véhicules permettent aujourd’hui de résoudre des problèmes de grandes tailles en intégrant les contraintes liées au métier. Dans cette thèse, nous nous intéressons à la résolution du problème riche de collectes et livraisons en camions complets avec des contraintes de synchronisation sur les ressources. Dans un premier temps, nous résolvons le problème de tournées de véhicules avec une méthode heuristique en deux phases. Dans un second temps, nous étudions l’intégration des contraintes liées aux temps de conduite des chauffeurs ainsi que l’ajout des pauses déjeuners aux tournées. Nous testons les algorithmes proposés sur des instances de la littérature et des instances réelles issues d’une application industrielle d’une entreprise de Travaux Publics. / In 2013, the transportation of materials for roads construction and earthwork represents more than half of the whole activity of in the public works sector. Optimization methods for vehicle routing problems allow to solve big-size problems with industrial sector constraints. In this thesis, we focus on solving the rich full truckload pickup and delivery problem with resource synchronization. First, we solve this vehicle routing problem with a two phase heuristic method. Then, we study the integration of regulation of drivers’ working hours and the addition of lunch breaks in routes of vehicles. These methods are tested on instances from the literature and real life instances from a public works company.

In this paper, we study a rich vehicle routing problem incorporating various complexities found in real-life applications. The General Vehicle Routing Problem (GVRP) is a combined load acceptance and generalised vehicle routing problem. Among the real-life requirements are time window restrictions, a heterogeneous vehicle fleet with different travel times, travel costs and capacity, multi-dimensional capacity constraints, order/vehicle compatibility constraints, orders with multiple pickup, delivery and service locations, different start and end locations for vehicles, and route restrictions for vehicles. The GVRP is highly constrained and the search space is likely to contain many solutions such that it is impossible to go from one solution to another using a single neighbourhood structure. Therefore, we propose iterative improvement approaches based on the idea of changing the neighbourhood structure during the search.

Diplomová práce se zabývá analýzou a výpočtem optimalizační úlohy z praxe. Jedná se o optimalizaci nočních linek vnitrostátní přepravy na území ČR. Cílem je nalezení řešení, které zefektivní organizaci těchto linek a usnadní práci lidí s nimi spojenou. Celý výpočet úlohy je inspirován okružním problémem s doručením a vyzvednutím (?Pickup and Delivery Problem?). Na výpočet problému jsou použity dva modely: model založený na hledání optimálního více produktového toku a model spočívající na výběru tras. Modely jsou založeny na rozdílných přístupech. Díky oběma modelům je možné si uvědomit, že na jednu optimalizační úlohu lze pohlížet z více stran a z obdržených výsledků si pak vytvořit ucelenější pohled na problém.

<p>Online retail sales and grocery/food orders have been breaking records every year. As a result, third-party delivery companies have found an opportunity to get their share from the growing transportation network. Electric vehicles (EVs) are becoming a preferable choice for such large delivery systems due to their environmental benefits. However, EVs have limited-service ranges; therefore, intra-route facilities are needed for EVs to stay operational. These facilities offer charging stations for EVs and storage areas for requests, e.g., food and packages. In this dissertation, we propose a novel <em>Pickup and Delivery Problem</em> (PDP) with EVs and transfers. There are requests to be picked up and delivered. EVs leave their origin depot, serve requests, and return to their destination depot. Unlike the generic PDP, intra-route facilities allow EVs to exchange requests. Thus, a request can be transported by more than one vehicle. In this dissertation, three new problems are introduced, and the following research questions are investigated: 1) "How valuable is to include intra-route facilities and allow transfers in a pickup and delivery network with EVs?", 2) "What is the cost of locating intra-route facilities randomly rather than finding the best locations while creating the routes for EVs?", and 3) "How much can drones improve the delivery speed in a pickup and delivery network with EVs and transfers?". A <em>Mixed-integer Linear Programming</em> (MILP) model and a <em>Simulated Annealing</em> (SA) algorithm are developed and compared with each other to answer the first question. For the second question, a MILP model is formulated; however, due to unreasonable computational runtimes, a SA algorithm and an <em>Adaptive Large Neighborhood Search</em> (ALNS) algorithm are proposed. Finally, a MILP model is developed for the hybrid-fleet problem. The overall results highlight that intra-route facilities shorten the total traveled distance in the PDP network by allowing exchanges and recharging.</p>

Dans cette thèse, nous nous intéressons à la gestion des flux de marchandises en zone urbaine aussi appelée logistique du dernier kilomètre, et associée à divers enjeux d’actualité : économique, environnemental, et sociétal. Quatre principaux acteurs sont concernés par ces enjeux : chargeurs, clients, transporteurs et collectivités, ayant chacun des priorités différentes (amélioration de la qualité de service, minimisation de la distance parcourue, réduction des émissions de gaz à effet de serre, …). Face à ces défis dans la ville, un levier d’action possible consiste à optimiser les tournées effectuées pour la livraison et/ou la collecte des marchandises. Trois types de flux urbains sont considérés : en provenance ou à destination de la ville, et intra-urbains. Pour les flux sortants et entrants dans la ville, les marchandises sont d’abord regroupées dans un entrepôt situé en périphérie urbaine. S’il existe plusieurs entrepôts, le problème de planification associé est de type Location Routing Problem (LRP). Nous en étudions une de ses variantes appelée Capacitated Location Routing Problem (CLRP). Dans cette dernière, en respectant la contrainte de capacité imposée sur les véhicules et les dépôts, la localisation des dépôts et la planification des tournées sont considérées en même temps. L’objectif est de minimiser le coût total qui est constitué du coût d’ouverture des dépôts, du coût d’utilisation des véhicules, et du coût de la distance parcourue. Pour tous les flux, nous cherchons également à résoudre un problème de tournées de type Pickup and Delivery Problem (PDP), dans lequel une flotte de véhicules effectue simultanément des opérations de collecte et de livraison. Nous nous sommes focalisés sur deux de ses variantes : la variante sélective où toutes les demandes ne sont pas toujours satisfaites, dans un contexte de demandes appairées et de sites contraints par des horaires d’ouverture et fermeture (Selective Pickup and Delivery Problem with Time Windows and Paired Demands, ou SPDPTWPD). La seconde variante étudiée est l’extension de la première en ajoutant la possibilité d’effectuer les transports en plusieurs étapes par l’introduction d’opérations d’échanges des marchandises entre véhicules en des sites de transfert (Selective Pickup and Delivery with Transfers ou SPDPT). Les objectifs considérés pour ces deux variantes de PDP sont de maximiser le profit et de minimiser la distance. Chaque problème étudié fait l’objet d’une description formelle, d’une modélisation mathématique sous forme de programme linéaire, puis d’une résolution par des méthodes exactes, heuristiques et/ou métaheuristiques. En particulier nous avons développé des algorithmes basés sur une métaheuristique appelée Particle Swarm Optimization, que nous avons hybridée avec de la recherche locale. Les approches sont validées sur des instances de différentes tailles issues de la littérature et/ou que nous avons générées. Les résultats sont analysés de façon critique pour mettre en évidence les avantages et inconvénients de chaque méthode. / In this thesis, we are interested in the management of goods flows in urban areas, also called last mile logistics, and associated with various current issues: economic, environmental, and societal. Four main stakeholders are involved by these challenges: shippers, customers, carriers and local authorities, each with different priorities (improving service quality, minimizing the travelling distance, reducing greenhouse gas emissions, etc.). Faced with these challenges in the city, one possible action lever is to optimize the routes for the pickup and/or delivery of goods. Three types of urban flows are considered: from or to the city, and intra-urban. For outgoing and incoming flows into the city, the goods are first grouped in a warehouse located on the suburban area of the city. If there are several warehouses, the associated planning problem is the Location Routing Problem (LRP). We are studying one of its variants called the Capacitated Location Routing Problem (CLRP). In this problem, by respecting the capacity constraint on vehicles and depots, the location of depots and route planning are considered at the same time. The objective is to minimize the total cost, which consists of the cost of opening depots, the cost of using vehicles, and the cost of the travelling distance. For all flows, we are also looking to solve a Pickup and Delivery Problem (PDP), in which a fleet of vehicles simultaneously carries out pickup and delivery operations. We focus on two of its variants: the selective variant where not all requests are satisfied, in a context of paired demands and time windows on sites (Selective Pickup and Delivery Problem with Time Windows and Paired Demands, or SPDPTWPD). The second studied variant is the extension of the first one by adding the possibility of carrying out transport in several stages by introducing operations for the exchange of goods between vehicles at transfer sites (Selective Pickup and Delivery with Transfers or SPDPT). The considered objectives for these two variants of PDP are to maximize profit and to minimize distance. Each studied problem is formally described, mathematically modelled as a linear program and then solved by exact, heuristic and/or metaheuristic methods. In particular, we have developed algorithms based on a metaheuristic called Particle Swarm Optimization, which we have hybridized with local search operators. The approaches are validated on instances of different sizes from the literature and/or on instances that we have generated. The results are critically analyzed to highlight the advantages and drawbacks of each method.

La présente thèse se déroule dans le cadre du projet ANR PRODIGE et est axée sur la recherche de stratégies permettant l’optimisation du transport en général et du transport routier de marchandises en particulier. Le problème de transport support de cette étude est le problème de collecte et livraison avec transbordement. Ce problème généralise plusieurs problèmes de transports classiques. Le transbordement y est utilisé comme levier de flexibilité et d’optimisation. Pour analyser et résoudre ce problème, les analyses sont effectuées suivant trois axes : le premier axe concerne l’élaboration d’un modèle analytique plus précisément d’un modèle mathématique en variables mixtes. Ce modèle permet de fournir dessolutions optimales au décisionnaire du transport mais présente l’inconvénient de nécessiter un temps de résolution qui croit exponentiellement avec la taille du problème. Cette limitation est levée par le deuxième axe d’étude qui permet de résoudre le problème de transport étudié par une méthode d’optimisation approchée tout en garantissant des solutions satisfaisantes.La méthode utilisée est une métaheuristique inspirée de la recherche à voisinages variables (VNS). Dans le troisième axe, l’ensemble des résultats obtenus dans la thèse sont testés en situation de transports réels via le projet PRODIGE. / The thesis is conducted under the ANR project PRODIGE and it is focused on seeking strategies allowing the optimization of transport in general and road freight transport in particular. The transportation problem support for this study is the pickup and delivery problem with transshipment.This problem generalizes several classical transportation problems.Transshipment is used as optimization and flexibility leverage. To study and solve this problem, analyzes are performed along three axes :the first objective concerns the development of an analytical model, more accurately a mathematical model with mixed variables. This model allows providing optimal solution to the decision maker, but has the disadvantage of requiring a time resolution that grows exponentially with the size of the problem. This limitation is overcome by the second line of the study that solves the transportation problem studied by an approximate optimization method while ensuring satisfactory solutions. The method used is a mataheuristic broadly followed the variables neighborhoods research principles. In the third objective, the overall results obtained in the thesis are tested in real transport situation via the PRODIGE project.