Efficiently generating k-best solutions to procurement auctions

Andrew Byde, Terence Kelly, Yunhong Zhou, Robert Tarjan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


Procurement executives often find it difficult to articulate their preferences and constraints regarding auctions, making it difficult to cast procurement decisions as straightforward optimization problems. This paper presents an efficient algorithm to aid decision support in such situations. Instead of trying to compute a single optimal solution for the auction winner determination problem, we generate many candidate solutions in ascending order of buyer expenditure. Standard techniques such as clustering and dominance pruning can then trim this list to a compact yet diverse menu of alternatives; other analyses can illuminate the cost of constraints and the competitive landscape. Our efficient solution-generation algorithm addresses sealed-bid procurement auctions with multiple suppliers and multiple types of goods available in multiple units. It supports multi-sourcing and volume discounts/surcharges in bids. Our algorithm may optionally incorporate certain classes of hard constraints, generating only solutions that satisfy them.

Original languageEnglish (US)
Title of host publicationAlgorithmic Aspects in Information and Management - 5th International Conference, AAIM 2009, Proceedings
Number of pages17
StatePublished - 2009
Externally publishedYes
Event5th International Conference on Algorithmic Aspects in Information and Management, AAIM 2009 - San Francisco, CA, United States
Duration: Jun 15 2009Jun 17 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5564 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other5th International Conference on Algorithmic Aspects in Information and Management, AAIM 2009
Country/TerritoryUnited States
CitySan Francisco, CA

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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