Collaboration in transportation

In this thesis, we investigate synergies between participants in transportation and distribution systems and we explore collaborative approaches to exploit these synergies to reduce transportation and distribution costs. Implementing collaborative approaches not only involves identifying and exploiting synergies between system participants, but also entails allocating any benefits fairly among them. We study collaboration in two environments: truckload transportation and vendor management inventory replenishment.;In truckload transportation synergies between loads may be exploited to increase truck utilization by reducing empty repositioning and thus reducing transportation costs. Shippers may exploit synergies by offering continuous move routes (with little or no empty repositioning) to carriers in return for reduced per mile charges. Carriers may exploit synergies by exchanging loads among themselves to reduce empty repositioning and thus increase truck utilization. In vendor managed inventory replenishment synergies between customers, due to their locations, usage rates, and storage capacities, may be exploited to reduce distribution costs by serving nearby customers on the same route at the same time.;By integrating non-cooperative and cooperative game theory methods with optimization techniques, we develop mechanisms to initiate and maintain collaborations. In contrast to earlier work on collaborative approaches, which focused on procurement, identifying and evaluating the value of synergies in transportation and distribution systems is difficult and requires optimization techniques. Furthermore, generic game theory models seldom lead to practically viable collaboration mechanisms. Therefore, we take the practical characteristics of the environment into consideration when developing collaborative solutions, thus ensuring that the resulting mechanisms are viable in that environment.;The first part of the thesis addresses the cost allocation problem of a collaborative truckload transportation procurement network. More specifically, we study a logistics network where shippers identify collaborative routes with few empty truck movements in order to negotiate better rates with a common carrier. We investigate how to allocate the cost savings, or equivalently the cost, of these routes among the members of the collaboration. First, we show that proportional allocation methods and allocation methods used in practice have several drawbacks, particularly in terms of stability. Next, we develop several cost allocation mechanisms that satisfy desirable game theoretic and have desirable practical properties.;In the second part of the thesis, we investigate collaboration opportunities among carriers. When several carriers have to satisfy truckload transportation requests from various shippers, they may reduce their transportation costs by exchanging requests. First, we focus on computing the minimum cost to satisfy all requests, i.e., the cost associated with the "perfect" carrier collaboration. To be able to do so, we have to simultaneously assign requests to carriers and determine the optimal routes for satisfying the requests assigned to each carrier. Next, we develop and analyze various exchange mechanisms that allow carriers to exchange requests in order to realize some of the potential costs savings. As carriers act selfishly, it may not be possible to reach the perfect collaboration.;In the last part of the thesis, we study vendor managed inventory replenishment. Vendor managed inventory replenishment is a collaboration between a supplier and its customers. Our focus is on allocating the distribution costs incurred by the supplier among the customers. Simple cost allocation methods ignore synergies between the customers, due to their locations, usage rates, and storage capacities. As a result, the price charged to a customer for distribution does not represent the actual cost of serving that customer, and therefore the company may lose existing customers to the competition or decline prospective customers. We design a mechanism capable of computing a cost-to-serve for each customer that properly accounts for the synergies among customers.