Genetic Algorithms versus Human Bidding Strategies for Auctions

Abstract

The increasing use of auctions has led to a growing interest in the subject. The objective of this paper is to develop a genetic algorithm to find optimum bidding strategies for Ausubel auctions. The algorithm provides the strategy (defined as the action to be taken under different market conditions) that maximizes pay off to the bidder. The algorithm is tested under a series of scenarios that differ in their composition of utility functions, number of bidders and quantity of lots auctioned. The results suggest that the approach leads to strategies that outperform sincere bidding systems.