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58
Winner determination in combinatorial auction generalizations
, 2002
"... Combinatorial markets where bids can be submitted on bundles of items can be economically desirable coordination mechanisms in multiagent systems where the items exhibit complementarity and substitutability. There has been a surge of recent research on winner determination in combinatorial auctions. ..."
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Cited by 157 (23 self)
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Combinatorial markets where bids can be submitted on bundles of items can be economically desirable coordination mechanisms in multiagent systems where the items exhibit complementarity and substitutability. There has been a surge of recent research on winner determination in combinatorial auctions. In this paper we study a wider range of combinatorial market designs: auctions, reverse auctions, and exchanges, with one or multiple units of each item, with and without free disposal. We first theoretically characterize the complexity. The most interesting results are that reverse auctions with free disposal can be approximated, and in all of the cases without free disposal, even finding a feasible solution is ÆÈcomplete. We then ran experiments on known benchmarks as well as ones which we introduced, to study the complexity of the market variants in practice. Cases with free disposal tended to be easier than ones without. On many distributions, reverse auctions with free disposal were easier than auctions with free disposal— as the approximability would suggest—but interestingly, on one of the most realistic distributions they were harder. Singleunit exchanges were easy, but multiunit exchanges were extremely hard. 1
CABOB: A fast optimal algorithm for combinatorial auctions
"... Combinatorial auctions where bidders can bid on bundles of items can lead to more economical allocations, but determining the winners iscomplete and inapproximable. We present CABOB, a sophisticated search algorithm for the problem. It uses decomposition techniques, upper and lower bounding (also a ..."
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Cited by 122 (26 self)
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Combinatorial auctions where bidders can bid on bundles of items can lead to more economical allocations, but determining the winners iscomplete and inapproximable. We present CABOB, a sophisticated search algorithm for the problem. It uses decomposition techniques, upper and lower bounding (also across components), elaborate and dynamically chosen bid ordering heuristics, and a host of structural observations. Experiments against CPLEX 7.0 show that CABOB is usually faster, never drastically slower, and in many cases drastically faster. We also uncover interesting aspects of the problem itself. First, the problems with short bids that were hard for the firstgeneration of specialized algorithms are easy. Second, almost all of the CATS distributions are easy, and become easier with more bids. Third, we test a number of random restart strategies, and show that they do not help on this problem because the runtime distribution does not have a heavy tail (at least not for CABOB). 1
Bidding languages for combinatorial auctions
 In Proc. 17th Intl. Joint Conference on Artif. Intell
, 2001
"... Combinatorial auctions provide a valuable mechanism for the allocation of goods in settings where buyer valuations exhibit complex structure with respect to substitutabilityand complementarity. Most algorithms are designed to work with explicit bids for concrete bundles of goods. However, logical bi ..."
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Cited by 91 (1 self)
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Combinatorial auctions provide a valuable mechanism for the allocation of goods in settings where buyer valuations exhibit complex structure with respect to substitutabilityand complementarity. Most algorithms are designed to work with explicit bids for concrete bundles of goods. However, logical bidding languages allow the expression of complex utility functions in a natural and concise way. We introduce a new, generalized language where bids are given by propositional formulae whose subformulae can be annotated with prices. This language allows bidder utilities to be formulated more naturally and concisely than existing languages. Furthermore, we outline a general algorithmic technique for winner determination for auctions that use this bidding language. 1
Learning the Empirical Hardness of Optimization Problems: The case of combinatorial auctions
 In CP
, 2002
"... We propose a new approach to understanding the algorithmspecific empirical hardness of optimization problems. In this work we focus on the empirical hardness of the winner determination probleman optimization problem arising in combinatorial auctionswhen solved by ILOG's CPLEX software. We co ..."
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Cited by 59 (20 self)
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We propose a new approach to understanding the algorithmspecific empirical hardness of optimization problems. In this work we focus on the empirical hardness of the winner determination probleman optimization problem arising in combinatorial auctionswhen solved by ILOG's CPLEX software. We consider nine widelyused problem distributions and sample randomly from a continuum of parameter settings for each distribution. First, we contrast the overall empirical hardness of the different distributions. Second, we identify a large number of distributionnonspecific features of data instances and use statistical regression techniques to learn, evaluate and interpret a function from these features to the predicted hardness of an instance.
Expressive commerce and its application to sourcing: How we conducted $35 billion of generalized combinatorial auctions
"... 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 i ..."
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Cited by 47 (8 self)
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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 winwin 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 harddollar savings plus numerous hardertoquantify 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.
Bundling Equilibrium in Combinatorial Auctions
, 2001
"... This paper analyzes individuallyrational ex post equilibrium in the VC (VickreyClarke) combinatorial auctions. If \Sigma is a family of bundles of goods, the organizer may restrict the participants by requiring them to submit their bids only for bundles in \Sigma. The \SigmaVC combinatorial aucti ..."
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Cited by 47 (8 self)
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This paper analyzes individuallyrational ex post equilibrium in the VC (VickreyClarke) combinatorial auctions. If \Sigma is a family of bundles of goods, the organizer may restrict the participants by requiring them to submit their bids only for bundles in \Sigma. The \SigmaVC combinatorial auctions (multigood auctions) obtained in this way are known to be individuallyrational truthtelling mechanisms. In contrast, this paper deals with nonrestricted VC auctions, in which the buyers restrict themselves to bids on bundles in \Sigma, because it is rational for them to do so. That is, it may be that when the buyers report their valuation of the bundles in \Sigma, they are in an equilibrium. We fully characterize those \Sigma that induce individually rational equilibrium in every VC auction, and we refer to the associated equilibrium as a bundling equilibrium. The number of bundles in \Sigma represents the communication complexity of the equilibrium. A special case of bundling equilibrium is partitionbased equilibrium, in which \Sigma is a field, that is, it is generated by a partition. We analyze the tradeoff between communication complexity and economic efficiency of bundling equilibrium, focusing in particular on partitionbased equilibrium.
The Exponentiated Subgradient Algorithm for Heuristic Boolean Programming
 IN PROC. IJCAI01
, 2001
"... Boolean linear programs (BLPs) are ubiquitous in AI. Satisfiability testing, planning with resource constraints, and winner determination in combinatorial auctions are all examples of this type of problem. Although increasingly wellinformed by work in OR, current AI research has tended to focu ..."
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Cited by 45 (2 self)
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Boolean linear programs (BLPs) are ubiquitous in AI. Satisfiability testing, planning with resource constraints, and winner determination in combinatorial auctions are all examples of this type of problem. Although increasingly wellinformed by work in OR, current AI research has tended to focus on specialized algorithms for each type of BLP task and has only loosely patterned new algorithms on effective methods from other tasks. In this paper we introduce a single generalpurpose local search procedure that can be simultaneously applied to the entire range of BLP problems, without modification. Although one might suspect that a generalpurpose algorithm might not perform as well as specialized algorithms, we find that this is not the case here. Our experiments show that our generic algorithm simultaneously achieves performance comparable with the state of the art in satisfiability search and winner determination in combinatorial auctions two very different BLP problems. Our algorithm is simple, and combines an old idea from OR with recent ideas from AI.
Side constraints and nonprice attributes in markets
 In: IJCAI2001 Workshop on Distributed Constraint Reasoning
, 2001
"... In most realworld (electronic) marketplaces, there are other considerations besides maximizing immediate economic value. We present a sound way of taking such considerations into account via side constraints and nonprice attributes. Side constraints have a significant impact on the complexity of m ..."
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Cited by 41 (15 self)
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In most realworld (electronic) marketplaces, there are other considerations besides maximizing immediate economic value. We present a sound way of taking such considerations into account via side constraints and nonprice attributes. Side constraints have a significant impact on the complexity of market clearing. Budget constraints, a limit on the number of winners, and XORconstraints make even noncombinatorial marketscomplete to clear. The latter two make marketscomplete to clear even if bids can be accepted partially. This is surprising since, as we show, even combinatorial markets with a host of very similar side constraints can be cleared in polytime. An extreme equality constraint makes combinatorial markets polytime clearable even if bids have to be accepted entirely or not at all. Finally, we present a way to take into account additional attributes using a bid reweighting scheme, and prove that it does not change the complexity of clearing. All of the results hold for auctions as well as exchanges, with and without free disposal. 1
Combinatorial auctions with structured item graphs
 In Proceedings of the Twenty First National Conference on Artificial Intelligence (AAAI 2004
, 2004
"... Combinatorial auctions (CAs) are important mechanisms for allocating interrelated items. Unfortunately, winner determination is NPcomplete unless there is special structure. We study the setting where there is a graph (with some desired property), with the items as vertices, and every bid bids on a ..."
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Cited by 25 (10 self)
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Combinatorial auctions (CAs) are important mechanisms for allocating interrelated items. Unfortunately, winner determination is NPcomplete unless there is special structure. We study the setting where there is a graph (with some desired property), with the items as vertices, and every bid bids on a connected set of items. Two computational problems arise: 1) clearing the auction when given the item graph, and 2) constructing an item graph (if one exists) with the desired property. 1 was previously solved for the case of a tree or a cycle, and 2 for the case of a line graph or a cycle. We generalize the first result by showing that given an item graph with bounded treewidth, the clearing problem can be solved in polynomial time (and every CA instance has some treewidth; the complexity is exponential in only that parameter). We then give an algorithm for constructing an item tree (treewidth 1) if such a tree exists, thus closing a recognized open problem. We show why this algorithm does not work for treewidth greater than 1, but leave open whether item graphs of (say) treewidth 2 can be constructed in polynomial time. We show that finding the item graph with the fewest edges is NPcomplete (even when a graph of treewidth 2 exists). Finally, we study how the results change if a bid is allowed to have more than one connected component. Even for line graphs, we show that clearing is hard even with 2 components, and constructing the line graph is hard even with 5.