1,721,016 research outputs found

    Resolution branch and bound and an application: The maximum weighted stable set problem

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    We propose a new resolution algorithm, called resolution branch and bound (RBB), where a branch-and-bound scheme is empowered by exploiting the information contained in a family of closed subproblems, collected by a full resolution phase. In particular, we use this information to define a new branching rule that seems able to reduce the risk of incurring inappropriate branchings. We apply RBB and the proposed branching rule to the maximum weighted stable set problem, as its features allow us to speed up a time-consuming step in the full resolution phase. To compute upper bounds, we generalize to the weighted case the polynomial time procedure provided by Mannino and Sassano [Mannino, C., A. Sassano. 1994. An exact algorithm for the maximum stable set problem. Computational Optim. Appl. 3 243-258] for the unweighted case. Computational results validate the effectiveness of the provided branching rule and the good performance of RBB on many DIMACS benchmarks

    Exploring the VCG mechanism in combinatorial auctions: The threshold revenue and the threshold-price rule

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    We explore interesting potential extensions of the Vickrey-Clarke-Groves (VCG) rule under the assumption of players with independent and private valuations and no budget constraints. First, we apply the VCG rule to a coalition of bidders in order to compute the second price of the coalition. Then, we introduce and formulate the problem of determining that partition of players into coalitions which maximize the auctioneer's revenue in the case whereby such coalitions take part to a VCG auction each one as a single agent; in particular, we provide an integer linear formulation of this problem. We also generalize this issue by allowing players to simultaneously belong to distinct coalitions in the case that players' valuation functions are separable. Finally, we propose some applications of these theoretical results. For instance, we exploit them to provide a class of new payment rules and to decide which bids should be defined as the highest losing ones in combinatorial auctions. © 2008 Elsevier B.V. All rights reserved

    Simulating combinatorial auctions with dominance requirement and loll bids through automated agents

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    When complementarity or substitutability relations exist among the items for auction, the use of combinatorial bidding (i.e. permitting players to bid on bundles of items) enhances the seller's revenue and ex-post market efficiency. We present a new first-price multi-round combinatorial format, where bids are subject to a stronger requirement than validity, and a new tool is applied, which in a sense generalizes the concept of waiver. The auction format is simulated through automated agents, assuming a model of bidders' beliefs about their opponents. We perform statistical analyses on simulation results, obtaining useful hints for the design of ascending combinatorial formats. (c) 2006 Elsevier B.V. All rights reserved

    Broadband investment and welfare under functional and ownership separation

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    We study how the vertical industry structure affects investment in network quality and social welfare, with a focus on the prospective deployment of high-speed broadband access networks (the so-called NGA). We model pros and cons of vertical separation, namely, procompetitive effects and loss of some efficiencies of vertical integration, and distinguish functional separation from ownership separation. Our findings challenge the presumption that (compared with vertical integration) vertical separation reduces investment incentives and involves a trade-off between promoting consumer surplus and ensuring investment. While investment is higher under ownership rather than functional separation, the latter may yield the highest social welfare among vertical industry structures. Furthermore, the incumbent may voluntarily opt for functional separation, but in some of these cases, prohibiting separation improves welfare. (C) 2014 Elsevier B.V. All rights reserved
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