Approximation and Online Algorithms: 4th International by Alexander A. Ageev, Alexander V. Kononov (auth.), Thomas

By Alexander A. Ageev, Alexander V. Kononov (auth.), Thomas Erlebach, Christos Kaklamanis (eds.)

This ebook constitutes the completely refereed post-proceedings of the 4th overseas Workshop on Approximation and on-line Algorithms, WAOA 2006, held in Zurich, Switzerland in September 2006 as a part of the ALGO 2006 convention event.

The 26 revised complete papers provided have been conscientiously reviewed and chosen from sixty two submissions. subject matters addressed by way of the workshop are algorithmic video game thought, approximation sessions, coloring and partitioning, aggressive research, computational finance, cuts and connectivity, geometric difficulties, inapproximability effects, mechanism layout, community layout, packing and overlaying, paradigms, randomization recommendations, real-world functions, and scheduling problems.

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Extra resources for Approximation and Online Algorithms: 4th International Workshop, WAOA 2006, Zurich, Switzerland, September 14-15, 2006. Revised Papers

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We recursively define a sequence of weights {yi }k−1 i=1 , with alternating signs which represent a shift in the demand supply of base stations to clients along the cycle. Start by setting y1 = , representing an increase of to the demand supplied by the base-stationvertex v1 to the client-vertex v2 . This increase of supply may not all be credited to vertex v2 due to interference, some of which are possibly due to base stations which are outside the cycle, which contribute to v2 ’s satisfaction.

Ym }, for every i = 1, . . , m, and j = 1, . . , n, and a budget B = L, while no interference are assumed. Clearly, a solution to k4k-BCPP is optimal if and only if the corresponding solution of the budgeted maximum coverage instance is optimal. 36 D. Amzallag, J. Naor, and D. 1 The Structure of BCPP Solutions Our algorithm is based on a combinatorial characterization of the solution set to BCPP3 (and in particular to k4k-BCPP ). The following lemma is a key component in the analysis of our approximation algorithm.

Clearly, a solution to k4k-BCPP is optimal if and only if the corresponding solution of the budgeted maximum coverage instance is optimal. 36 D. Amzallag, J. Naor, and D. 1 The Structure of BCPP Solutions Our algorithm is based on a combinatorial characterization of the solution set to BCPP3 (and in particular to k4k-BCPP ). The following lemma is a key component in the analysis of our approximation algorithm. Lemma 1. Every solution to the k4k-budgeted cell planning problem can be transformed to a solution in which the number of clients that are covered by more than one base station is at most the number of opened base stations.

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