2000/10/24 by Karhan Akcoglu, Akcoglu, Karhan, James Aspnes +7 · 1 citation
Business, Management and Accounting · Computer Science · Decision Sciences · #Auction Theory and Applications #Computational Engineering #Consumer Market Behavior and Pricing #Data Structures and Algorithms (cs.DS) #F.2.0 #FOS: Computer and information sciences #Finance #J.4 #and Science (cs.CE) #cs.CE #cs.DS
paper · pdf · doi:10.48550/arxiv.cs/0010031
arxiv created 2000/10/24 · openalex publication_date 2000/10/24 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Two general algorithms based on opportunity costs are given for approximating a revenue-maximizing set of bids an auctioneer should accept, in a combinatorial auction in which each bidder offers a price for some subset of the available goods and the auctioneer can only accept non-intersecting bids. Since this problem is difficult even to approximate in general, the algorithms are most useful when the bids are restricted to be connected node subsets of an underlying object graph that represents which objects are relevant to each other. The approximation ratios of the algorithms depend on structural properties of this graph and are small constants for many interesting families of object graphs. The running times of the algorithms are linear in the size of the bid graph, which describes the conflicts between bids. Extensions of the algorithms allow for efficient processing of additional constraints, such as budget constraints that associate bids with particular bidders and limit how many bids from a particular bidder can be accepted.