Theses and Dissertations


Zhuoxiu Zhang

Issuing Body

Mississippi State University


Jin, Mingzhou

Committee Member

Eksioglu, Burak

Committee Member

Kutanoglu, Erthan

Committee Member

Eksioglu, Sandra

Date of Degree


Document Type

Dissertation - Open Access


Industrial Engineering

Degree Name

Doctor of Philosophy


James Worth Bagley College of Engineering


Department of Industrial and Systems Engineering


This dissertation examines an iterative multi-attribute auction for multi-unit procurement in the first part. A multi-unit allocation problem that allows order split among suppliers is formulated to improve the market efficiency. Suppliers are allowed to provide discriminative prices over units based on their marginal costs. A mechanism called Iterative Multiple-attribute Multiple-unit Reverse Auction (IMMRA) is proposed based on the assumption of the modified myopic best-response strategies. Numerical experiment results show that the IMMRA achieves market efficiency in most instances. The inefficiency occurs occasionally on the special cases when cost structures are significantly different among suppliers. Numerical results also show that the IMMRA results in lower buyer payments than the Vickrey-Clarke-Grove (VCG) payments in most cases. In the second part, two sequential auctions with the Vickrey-Clarke-Grove (VCG) mechanism are proposed for two buyers to purchase multiple units of an identical item. The invited suppliers are assumed to have capacity constraints of providing the required demands. Three research problems are raised for the analysis of the sequential auctions: the suppliers' expected payoff functions, the suppliers' bidding strategies in the first auction, and the buyers' procurement costs. Because of the intrinsic complexity of the problems, we limit our study to a duopoly market environment with two suppliers. Both suppliers’ dominant bidding strategies are theoretically derived. With numerical experiments, suppliers’ expected profits and buyers’ expected procurement costs are empirically analyzed.