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Algorithm for optimal winner determination in combinatorial auctions

Tuomas Sandholm
- 01 Feb 2002 - 
- Vol. 135, Iss: 1, pp 1-54
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TLDR
The algorithm allows combinatorial auctions to scale up to significantly larger numbers of items and bids than prior approaches to optimal winner determination by capitalizing on the fact that the space of bids is sparsely populated in practice.
About
This article is published in Artificial Intelligence.The article was published on 2002-02-01 and is currently open access. It has received 1045 citations till now. The article focuses on the topics: Combinatorial auction & Common value auction.

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Book ChapterDOI

Generalized knapsack solvers for multi-unit combinatorial auctions: analysis and application to computational resource allocation

TL;DR: A solver whose pseudo-polynomial time and memory requirements are linear in three of four natural measures of problem size: number of agents, length of bids, and units of each resource is presented, which offers advantages over more elaborate approaches developed for high-dimensional problems.
Book ChapterDOI

Optimal Clearing of Supply/Demand Curves

TL;DR: This work presents a fast polynomial-time algorithm for nondiscriminatory clearing, and shows that discriminatory clearing is NP-complete (even in a very special case), and it is shown that in the more restricted setting of linear curves, even discriminatory markets can be cleared fast inPolynomial time.

Solving combinatorial auctions with temporal constraints in economic agents

Maria Gini, +1 more
TL;DR: In this article, the authors consider the problem of self-interested economic agents who must negotiate with each other to carry out their plans, and describe the high-level design of an agent that can act as a customer in this environment, and describes the decision behaviors such an agent must implement to maximize its utility.
Journal ArticleDOI

Service customization under capacity constraints: an auction-based model

TL;DR: Experimental results indicate that customization solutions computed by the proposed model are very close to the optimal one.
Journal ArticleDOI

Strategic negotiation for sharing a resource between two agents

TL;DR: A strategic negotiation model that enables self‐motivated rational agents to share resources and performs as well as a centralized scheduler and also has the property of balancing the resources' usage is proposed.
References
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Book

Introduction to Algorithms

TL;DR: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures and presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers.
Book ChapterDOI

Reducibility Among Combinatorial Problems

TL;DR: The work of Dantzig, Fulkerson, Hoffman, Edmonds, Lawler and other pioneers on network flows, matching and matroids acquainted me with the elegant and efficient algorithms that were sometimes possible.
Book

Integer programming

TL;DR: The principles of integer programming are directed toward finding solutions to problems from the fields of economic planning, engineering design, and combinatorial optimization as mentioned in this paper, which is a standard of graduate-level courses since 1972.
Journal ArticleDOI

Incentives in Teams

Theodore Groves
- 01 Jul 1973 - 
TL;DR: This paper analyzes the problem of inducing the members of an organization to behave as if they formed a team and exhibits a particular set of compensation rules, an optimal incentive structure, that leads to team behavior.