Vidal's libraryTitle: | Expressive Commerce and Its Application to Sourcing: How We Conducted \$35 Billion of Generalized Combinatorial Auctions |
Author: | Tuomas Sandholm |
Journal: | AI Magazine |
Volume: | 28 |
Number: | 3 |
Pages: | 45--58 |
Year: | 2007 |
Abstract: | Sourcing professionals buy several trillion dollars worth of goods and services yearly. We introduced a new paradigm called expressive commerce and applied it to sourcing. It combines the advantages of highly expressive human negotiation with the advantages of electronic reverse auctions. The idea is that supply and demand are expressed in drastically greater detail than in traditional electronic auctions, and are algorithmically cleared. This creates a Pareto efficiency improvement in the allocation (a win-win between the buyer and the sellers) but the market clearing problem is a highly complex combinatorial optimization problem. We developed the world’s fastest tree search algorithms for solving it. We have hosted \$35 billion of sourcing using the technology, and created \$4.4 billion of hard-dollar savings plus numerous harder-to-quantify benefits. The suppliers also benefited by being able to express production efficiencies and creativity, and through exposure problem removal. Supply networks were redesigned, with quantitative understanding of the tradeoffs, and implemented in weeks instead of months. |
@Article{sandholm07a,
author = {Tuomas Sandholm},
title = {Expressive Commerce and Its Application to Sourcing:
How We Conducted \$35 Billion of Generalized
Combinatorial Auctions},
journal = {{AI} Magazine},
year = 2007,
volume = 28,
number = 3,
pages = {45--58},
abstract = {Sourcing professionals buy several trillion dollars
worth of goods and services yearly. We introduced a
new paradigm called expressive commerce and applied
it to sourcing. It combines the advantages of highly
expressive human negotiation with the advantages of
electronic reverse auctions. The idea is that supply
and demand are expressed in drastically greater
detail than in traditional electronic auctions, and
are algorithmically cleared. This creates a Pareto
efficiency improvement in the allocation (a win-win
between the buyer and the sellers) but the market
clearing problem is a highly complex combinatorial
optimization problem. We developed the world’s
fastest tree search algorithms for solving it. We
have hosted \$35 billion of sourcing using the
technology, and created \$4.4 billion of hard-dollar
savings plus numerous harder-to-quantify
benefits. The suppliers also benefited by being able
to express production efficiencies and creativity,
and through exposure problem removal. Supply
networks were redesigned, with quantitative
understanding of the tradeoffs, and implemented in
weeks instead of months.},
url = {http://jmvidal.cse.sc.edu/library/sandholm07a.pdf}
}
Last modified: Wed Mar 9 10:16:49 EST 2011