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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Journal ArticleDOI
Winner Determination in Combinatorial Auctions using Hybrid Ant Colony Optimization and Multi-Neighborhood Local Search
TL;DR: This paper proposes a hybrid Ant Colony Optimization with a novel Multi-Neighborhood Local Search (ACO-MNLS) algorithm for solving Winner Determination Problem (WDP) in combinatorial auctions and compares the efficiency of ACO- MNLS in the terms of solution quality and computational time.
Proceedings ArticleDOI
Robust solutions for combinatorial auctions
Alan Holland,Barry O'Sullivan +1 more
TL;DR: An auction model that uses a form of leveled commitment contract to improve solution reparability by facilitating backtracking on winning bids by the bid-taker is introduced and the trade-off between robustness and revenue in different economically motivated auction scenarios is examined.
Proceedings ArticleDOI
Towards Automated Procurement via Agent-Aware Negotiation Support
TL;DR: iBundler is described, an agent-aware negotiation service to solve the winner determination problem considering buyers and providers' constraints and preferences in industrial procurement.
Journal ArticleDOI
Benefits of in-vehicle consolidation in less than truckload freight transportation operations
TL;DR: In this paper, a branch-and-price algorithm is used to solve a multi-commodity one-to-one pickup-anddelivery vehicle routing problem that is solved using a branch and price algorithm.
Proceedings Article
Information-theoretic approaches to branching in search
Andrew Gilpin,Tuomas Sandholm +1 more
TL;DR: Four families of methods for selecting what question to branch on are presented, all information-theoretically motivated to reduce uncertainty in remaining subproblems and one is about branching using carefully constructed linear inequality constraints over sets of variables.
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.
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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.
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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.