Performance analysis of reverse auction mechanisms based on Petri nets

As a methodology of resource location and allocation, reverse auctions are one of the most important activities in supply chains. There are four main auction mechanisms in auction theory, ascending-bid auctions, descending-bid auctions, first-price and sealed-bid auctions, and second-price and sealed-bid auctions. Recently, procurement bidding auctions have been widely studied in the aspects of bidding strategy, auction mechanism with different characteristics, behavior and psychology, collusion and its detection method, and the risk management. However, studies addressing the issue of which is the better reverse auction mechanism in cost-down performance are rarely documented. In this work, simulations are performed to study the integrated process of a dynamic online reverse auction and a static sealed-bid reverse auction using timed colored Petri nets based on the contribution of event management and workflow in Petri net theory. In the Petri net models, colored tokens represent bidders' related data instantly, and transition nodes are in charge of executing bidding process rules whenever they are enabled. In addition, three programming methods including bidder's bid and auctioneer's winner set decision-making methods are embedded in the bidding process rules. Then, a hierarchical Petri net model is employed to compare cost-down range performance of dynamic online reverse auction and a static sealed-bid reverse auction, respectively. By modeling a comparison rule through a transition node, a reverse auction mechanism with better cost-down performance can be revealed based on the convergent simulation results.