This dissertation focuses on the bidding problem in combinatorial auctions with particular application to the freight transportation contract procurement problem. Combinatorial auctions are auctions in which a set of heterogeneous items are sold simultaneously and in which bidders can bid for combinations of items. These auctions involve many difficult problems for both auctioneers and bidders and have received recent attention from computer scientists, operations researchers and economists. Large shippers have begun to use this method to procure services from trucking companies by selling contracts for delivery routes.
This dissertation analyzes the impact of the combinatorial auction procurement method on both shippers and carriers. I demonstrate that bidders have more complicated optimization problems than auctioneers in combinatorial auctions. The bid construction problem, i.e. how bidders identify and construct beneficial bids, is very difficult to solve and remains an open question. This dissertation investigates this problem and proposes an optimization-based approximation method that involves solving an NP-hard problem a single time, yielding significant improvements in computational efficiency.
I also examine the current state of the trucking and third party logistics industries. The trucking industry is very competitive and small carriers are operating under thin margins. This dissertation addresses this issue by proposing an auction-based collaborative carrier network in which participating carriers identify inefficient lanes and exchange them with partners. This is shown to be Pareto efficient. I then discuss decision problems related to how carriers identify inefficient operations and make and select bids. This represents an effort to utilize an advanced auction mechanism to enhance carriers’ operational efficiencies in e-commerce.
