Truck-based freight transportation continues to play a vital role in the delivery of goods in the United States. Despite its size and importance, the truck transportation industry continues to struggle with fulfilling transportation requests in an efficient and sustainable manner. One potential solution to alleviate many of the current truck industry problems is for transportation service providers (TSPs) to collaborate by sharing volume, resources, and facilities. This research introduces the Transportation Service Provider Collaboration Problem (TSP-CP) to demonstrate the benefits of using optimal freight routing and consolidation decisions for collaborating TSPs. A mathematical model for the TSP-CP is introduced to describe the problem in detail. Additionally, two separate adaptive large neighborhood search (ALNS) heuristics are developed to provide solutions to industry representative problem instances. Finally, the benefits and insights achieved by enabling collaboration between TSPs using the TSP-CP are identified using industry representative data sets. The representative data sets were derived from actual freight data provided by a freight pooling company that manages collaboration among TSPs. Carriers were chosen from the industry data to evaluate collaborative partnerships and to gain insights on the effects of partnership characteristics on overall benefit as well as the benefits obtained by individual carriers. The computational results suggested collaboration among TSPs offers the potential for substantial reductions in the total distance required to deliver all loads, in the number miles that were traveled completely empty, and the number of containers required for delivery compared to individual performance. Additionally, collaboration increased delivery resource capacity utilization as measured by the percentage of weighted full miles. Detailed analysis of the results from the TSP-CP revealed new insights into the collaboration between full truckload and less-than truckload carriers that have not been quantified or highlighted in previous research. These insights included the effect that an individual carrier's type and size had on the amount of benefit received to each carrier. Finally, the results highlighted the importance of building collaborative partnerships that consider a carrier's geographic location. / Ph. D.

La logistique collaborative est récemment devenue un élément important pour beaucoup d'entreprises afin d'améliorer l'efficacité de leur chaîne logistique. Dans cette thèse, nous étudions les possibilités offertes par les problèmes de collectes et livraisons pour améliorer les performances des chaînes logistiques grâce au transport collaboratif. La thèse est inscrite dans un projet européen nommé SCALE (Step Change in Agri-food Logistics Ecosystem). Dans un premier temps, deux métaheuristiques sont proposées et étudiées pour résoudre le problème de collectes et livraisons avec transbordements. Celles-ci sont comparées aux travaux de la littérature et permettent d’améliorer les résultats sur certaines instances. Dans un deuxième temps, un modèle pour un problème de collectes et livraisons (PDVRP) est proposé. Celui-ci est utilisé pour étudier les bénéfices de la collaboration sur le transport. Il est appliqué sur des données générées aléatoirement et sur des données réelles issues du projet SCALE. Enfin troisièmement, un modèle pour un PDVRP particulier est présenté. Dans ce modèle, les marchandises doivent passer par exactement deux points de transbordement entre les points de collecte et les points de livraison. Ce problème est inspiré d'une seconde étude de cas réalisée dans le cadre du projet SCALE. Ceci permet de mettre en évidence l’intérêt de la collaboration et du transbordement dans le domaine du transport de marchandises. / Collaborative logistics have become recently an important element for many companies to improve their supply chains efficiency. In this thesis, we study pickup and delivery problems to improve supply chains efficiency thanks to collaborative transportation. The thesis was part of the European project SCALE (Step Change in Agri-food Logistics Ecosystem). Firstly, two metaheuristics are proposed and studied to solve the Pickup and Delivery Problem with Transshipments. These metaheuristics are compared with literature works and the results of several instances are improved. Secondly, a mathematical model for a pickup and delivery problem (PDVRP) is proposed. This model is used to study the benefits of collaboration on transportation. It is applied on random data and on a case study from SCALE with real data. Finally, a model for a particular PDVRP is presented. In this model, the shipments have to cross exactly two transshipments nodes between their pickup and delivery points. This problem is inspired by a second case study made during the project SCALE. This allows to highlight the importance of collaboration and transshipment in the field of goods transportations.