The market economy deals with many interacting agents such as buyers and sellers who are autonomous intelligent agents pursuing their own interests. One such multi-agent system (MAS) that plays an important role in auctions is the combinatorial auctioning system (CAS). We use this framework to define our concept of fairness in terms of what we call as "basic fairness" and "extended fairness". The assumptions of quasilinear preferences and dominant strategies are taken into consideration while explaining fairness. We give an algorithm to ensure fairness in a CAS using a Generalized Vickrey Auction (GVA). We use an algorithm of Sandholm to achieve optimality. Basic and extended fairness are then analyzed according to the dominant strategy solution concept.
Combinatorial Auctions are auctions where bidders can place bids on combinations of items, called packages or bundles, rather than just on individual items. In this paper we extend this concept to distributed system, by proposing a Distributed Combinatorial Auctioning System consisting of auctioneers and bidders who communicate by message-passing. We also propose a fair division algorithm that is based on our DCAS concept and model. Our model consist of auctioneers that are distributed in the system each having local bidders. Auctioneers collect local bids for the bundles. One of the auctioneers acts obtains all the bids from other auctioneers, and performs the computations necessary for the combinatorial auction. We also briefly discuss how basic and extended fairness are implemented in resource allocation by our algorithm.