Coordinating Multi-Attribute Procurement Auctions in Finite Capacity Assembly Environments

Research on reverse auctions for procurement has traditionally ignored the temporal and finite capacity constraints under which manufacturers operate. We consider the problem faced by a manufacturer that procures multiple key components from a number of possible suppliers through multi-attribute reverse auctions. Bids submitted by prospective suppliers include a price and a delivery date. The manufacturer has to select a combination of supplier bids that will maximize its overall profit. The manufacturer's profit is determined by the revenue generated by the products it sells, the costs of the components it purchases as well as late delivery penalties it incurs if it fails to deliver products in time to its own customers. We provide a formal model of this important class of problems, discuss its complexity and introduce rules that can be used to efficiently prune the resulting search space. We proceed to show that our model can be characterized as a pseudo-early/tardy scheduling problem and use this observation to build an efficient heuristic search procedure. Computational results show that our heuristic procedure typically yields solutions that are only a few percent from the optimum. They further indicate that taking into account the manufacturer's capacity significantly improves its bottom line.