Reverse Ant Colony Optimization for the Winner Determination Problem in Combinatorial Auctions

Abstract

An auction is an effective process of trading items among bidders and sellers. Combinatorial auctions are auctions in which bidders can place bids on a bundle of items rather than bidding on a single item. As a result, they lead to more efficient allocations compared to traditional auctions. Determining the winners whose bids maximize the auctioneer's profit is known as the winner determination problem. The problem is NP-complete since it is not possible to solve it in polynomial time as the inputs increase. In this paper, reverse ant colony optimization algorithm is proposed for the problem which focuses on maximization of the ants' route instead of minimization of the regular version. The experimental results are compared using different size data sets with a previously proposed genetic algorithm and a random search algorithm. The experiments indicate that, as the search space expands, the proposed algorithm finds better solutions than the others.