Information Processing Letters
Computationally Manageable Combinational Auctions
Management Science
An efficient approximate algorithm for winner determination in combinatorial auctions
Proceedings of the 2nd ACM conference on Electronic commerce
Towards a universal test suite for combinatorial auction algorithms
Proceedings of the 2nd ACM conference on Electronic commerce
Algorithm for optimal winner determination in combinatorial auctions
Artificial Intelligence
Truth revelation in approximately efficient combinatorial auctions
Journal of the ACM (JACM)
A note on greedy algorithms for the maximum weighted independent set problem
Discrete Applied Mathematics
Taming the Computational Complexity of Combinatorial Auctions: Optimal and Approximate Approaches
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Improved Algorithms for Optimal Winner Determination in Combinatorial Auctions and Generalizations
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Combinatorial Auctions: A Survey
INFORMS Journal on Computing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
CABOB: a fast optimal algorithm for combinatorial auctions
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Improving efficiency in multiple-unit combinatorial auctions: Bundling bids from multiple bidders
Decision Support Systems
Consensus-based decentralized auctions for robusttask allocation
IEEE Transactions on Robotics
Centralized and distributed task allocation in multi-robot teams via a stochastic clustering auction
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
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The winner determination problem (WDP) in combinatorial auctions is the problem of, given a finite set of combinatorial bids {\cal B}, finding a feasible subset {\cal B}′ of {\cal B} with a maximum revenue. WDP is known to be equivalent to the maximum weight set packing problem, and hard to approximate by polynomial time algorithms. This paper proposes three heuristic bid ordering schemes for solving WDP; the first two schemes take into account the number of goods shared by conflicting bids, and the third one is based on a recursive application of such local heuristic functions. We conducted several experiments to evaluate the goodness of the proposed schemes. The result of experiments implies that the first two schemes are particularly effective to improve the performance of the resulting heuristic search procedures. More concretely, they are scalable compared with the conventional linear programming (LP) relaxation based schemes, and could quickly provide an optimum solution under optimization schemes such as the branch-and-bound method. In addition, they exhibit a good anytime performance competitive to the LP-based schemes, although it is sensitive to configurable parameters controlling the strength of contributions of bid conflicts to the resultant bid ordering schemes.