Strategic Bidding in Knapsack Auctions
Abstract
This paper examines knapsack auctions as a method to solve the knapsack problem with incomplete information, where object values are private and sizes are public. We analyze three auction types-uniform price (UP), discriminatory price (DP), and generalized second price (GSP)-to determine efficient resource allocation in these settings. Using a Greedy algorithm for allocating objects, we analyze bidding behavior, revenue and efficiency of these three auctions using theory, lab experiments, and AI-enriched simulations. Our results suggest that the uniform-price auction has the highest level of truthful bidding and efficiency while the discriminatory price and the generalized second-price auctions are superior in terms of revenue generation. This study not only deepens the understanding of auction-based approaches to NP-hard problems but also provides practical insights for market design.
Cite
@article{arxiv.2403.07928,
title = {Strategic Bidding in Knapsack Auctions},
author = {Peyman Khezr and Vijay Mohan and Lionel Page},
journal= {arXiv preprint arXiv:2403.07928},
year = {2024}
}