Managing Constraints and Preferences for Winner Determination in Multi-attribute Reverse Auctions

Abstract

Multi-Attribute Reverse Auctions (MARAs) are considered an excellent way to buy and sell efficiently. However, eliciting the buyer's requirements and preferences as well as determining the winner, are both challenging tasks. In this paper, we propose a multi-round and semi-sealed MARA auction system, capable of determining the winner given a set of user's preferences and requirements. This system is capable of managing qualitative, quantitative and conditional preferences together with constraints. For that, we use the constrained Tradeoffs-enhanced Conditional Preference Networks (constrained TCP-nets) graphical model for representing constraints as well as qualitative and conditional preferences, and Multi-Attribute Utility Theory (MAUT) for dealing with quantitative preferences. Determining the winners of the auction will then be achieved using the backtrack search algorithm we use for solving constrained TCP-nets.