A preference-based, multi-unit auction for pricing and capacity allocation

Abstract

We study a pricing and allocation problem of a seller of multiple units of a homogeneous item, and present a semi-market mechanism in the form of an iterative ascending-bid auction. The auction elicits buyers' preferences over a set of options offered by the seller, and processes them with a random-priority assignment scheme to address buyers' "fairness" expectations. The auction's termination criterion is derived from a mixed-integer programming formulation of the preference-based capacity allocation problem. We show that the random priority-and preference-based assignment policy is a universally truthful mechanism which can also achieve a Pareto-efficient Nash equilibrium. Computational results demonstrate that the auction mechanism can extract a substantial portion of the centralized system's profit, indicating its effectiveness for a seller who needs to operate under the "fairness" constraint.

Walrasian equilibria from an optimization perspective: A guide to the literature

“…In some of these markets the auctioneer computes prices that are in a competitive equilibrium with linear and anonymous prices (aka. a Walrasian equilibrium), in others Walrasian prices even lead to efficiency losses (Özer & Özturan, 2009; Lessan & Karabatı, 2018; Bichler et al, 2018; Meeus et al, 2009; Madani & Van Vyve, 2015). This raises the question, which market characteristics admit Walrasian equilibria.…”

Mechanism Design of Unknown Bidding Preference and Discrete Cost Structure in Multi-Attribute Reverse Auctions

“…The outcome of MARA would not be determined until the termination rule is reached. Since procurement cost and delivery time are the most important factors for firms to achieve the goal of lean manufacturing [13], [32], we assume that each supplier has a limited capacity of the goods and discrete cost values associated with the supply quantity and delivery time. Without loss of generality, the unit cost could be discounted in terms of the supply quantity and delivery time [25].…”