Increased competitiveness with other transport systems and declining operation margins have motivated freight forwarders in the air cargo transport industry to look into horizontal collaboration. This thesis focuses on developing a fully integrated five phase auction based coopetition model, a form of horizontal collaboration where competition is preserved. A combinatorial auction is used to exchange transportation requests without having to reveal critical company information. Freight forwarders submit requests into an auction pool, where they are grouped into attractive bundles by a central planner and offered for auction. The request selection and bundling procedures, developed in this thesis, are based on the time windows of the request deliveries. A freight forwarder’s bid on each bundle is equal to the marginal profit of that bundle, which is obtained by solving two NP-hard routing problems with a simulated annealing and large neighbourhood search metaheuristic. A unique aspect of the auction, is that the dock capacity of the ground handlers is taken into account, which helps to alleviate truck congestion at the ground handlers. The potential of the auction based coopetition model is shown for an air cargo supply chain scenario. There is a clear increase in profitability for the collaborating freight forwarders, because the auction model decreases the transportation costs for the entire coalition. This cost reduction is achieved by an increase in transport efficiency, while the collaboration disadvantages as seen in literature are limited.

This bachelor thesis is about binary error-correcting codes. A binary code is a collection words with the same length n that consists only of zeroes and ones. The error-correcting quality of a code is determined by the Hamming distance d of a code. A classical question in coding theory is: What is the maximum number of codewords in a code with length n and Hamming distance d? This maximum is denoted with A(n,d). Determining A(n,d) is quite difficult and often we have to make due with lower and upper bounds on A(n,d). In this thesis we compare six different bounds for finding an upper bound on A(n,d), give a detailed description of each bound, a proof and a clarifying example. The main focus of this thesis lies on the linear programming bound (with extra constraints). For d=4 we dive deeper into the linear programming bound and the Krawtchouck polynomials it uses. Finally we draw some conclusions from the comparisons of the different types of bounds.