2,558 research outputs found

    Improved approximation algorithm for k-level UFL with penalties, a simplistic view on randomizing the scaling parameter

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    The state of the art in approximation algorithms for facility location problems are complicated combinations of various techniques. In particular, the currently best 1.488-approximation algorithm for the uncapacitated facility location (UFL) problem by Shi Li is presented as a result of a non-trivial randomization of a certain scaling parameter in the LP-rounding algorithm by Chudak and Shmoys combined with a primal-dual algorithm of Jain et al. In this paper we first give a simple interpretation of this randomization process in terms of solving an aux- iliary (factor revealing) LP. Then, armed with this simple view point, Abstract. we exercise the randomization on a more complicated algorithm for the k-level version of the problem with penalties in which the planner has the option to pay a penalty instead of connecting chosen clients, which results in an improved approximation algorithm

    Approximation algorithms for Capacitated Facility Location Problem with Penalties

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    In this paper, we address the problem of capacitated facility location problem with penalties (CapFLPP) paid per unit of unserved demand. In case of uncapacitated FLP with penalties demands of a client are either entirely met or are entirely rejected and penalty is paid. In the uncapacitated case, there is no reason to serve a client partially. Whereas, in case of CapFLPP, it may be beneficial to serve a client partially instead of not serving at all and, pay the penalty for the unmet demand. Charikar et. al. \cite{charikar2001algorithms}, Jain et. al. \cite{jain2003greedy} and Xu- Xu \cite{xu2009improved} gave 33, 22 and 1.85261.8526 approximation, respectively, for the uncapacitated case . We present (5.83+ϵ)(5.83 + \epsilon) factor for the case of uniform capacities and (8.532+ϵ)(8.532 + \epsilon) factor for non-uniform capacities

    A Review of ISO New England's Proposed Market Rules

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    This report reviews the proposed rules for restructured wholesale electricity markets in New England. We review the market rules, both individually and collectively, and identify potential problems that might limit the efficiency of these markets. We examine alternatives and identify the key tradeoffs among alternative designs. We believe that the wholesale electricity market in New England can begin on December 1, 1998. However, improvements are needed for long-run success. We have identified four major recommendations: 1. Switch to a multi-settlement system. 2. Introduce demand-side bidding. 3. Adopt location-based transmission congestion pricing, especially for the import/export interfaces. 4. Fix the pricing of the ten minute spinning reserves.Auctions; Multiple Object Auctions; Electricity Auctions

    Configuring Multi-Stage Global Supply Chains with Uncertain Demand

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    Approximation Algorithms for Capacitated Location Routing

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    An approximation algorithm for an optimization problem runs in polynomial time for all instances and is guaranteed to deliver solutions with bounded optimality gap. We derive such algorithms for different variants of capacitated location routing, an important generalization of vehicle routing where the cost of opening the depots from which vehicles operate is taken into account. Our results originate from combining algorithms and lower bounds for different relaxations of the original problem, and besides location routing we also obtain approximation algorithms for multi-depot capacitated vehicle routing by this framework. Moreover, we extend our results to further generalizations of both problems, including a prize-collecting variant, a group version, and a variant where cross-docking is allowed. We finally present a computational study of our approximation algorithm for capacitated location routing on benchmark instances and large-scale randomly generated instances. Our study reveals that the quality of the computed solutions is much closer to optimality than the provable approximation factor
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