Algorithm for optimal winner determination in combinatorial auctions
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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.read more
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Economically-augmented job shop scheduling
TL;DR: EJSP is presented as an example of a coordination problem among self-interested agents with private information and the need for solution mechanisms, which give the agents no incentive to lie is emphasized.
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Bidding Support for Computational Resources
Xavier Vilajosana,Joan Manuel Marquès,Ruby Krishnaswamy,Angel A. Juan,Nejla Amara-Hachmi,Leandro Navarro +5 more
TL;DR: A bidding specification language and support tools for grid-oriented open resource marketplaces based on trees that permit bidders to express their preferences for grid resources by means of logical operators and reduces the complexity of existing bidding languages.
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Towards generic solver of combinatorial optimization problems with autonomous agents in P2P networks
TL;DR: The result of experiments indicates that the proposed parallel processing scheme significantly improves the performance of the underlying B&B scheme by adaptively switching exploring policies adopted by each agent participating to the problem solving.
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Co-evolutionary Agents in Combinatorial Sealed-bid Auctions for Spectrum Licenses Markets
TL;DR: This work has developed a simulator of a combinatorial first-price sealed-bid auction and the bidding behaviour has been simulated by the application of co-evolutionary dynamics in an agent-based model.
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
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.