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16
Primaldual approximation algorithms for metric facility location and kmedian problems
 Journal of the ACM
, 1999
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The Online Median Problem
 In Proceedings of the 41st Annual IEEE Symposium on Foundations of Computer Science
, 2000
"... We introduce a natural variant of the (metric uncapacitated) kmedian problem that we call the online median problem. Whereas the kmedian problem involves optimizing the simultaneous placement of k facilities, the online median problem imposes the following additional constraints: the facilities ar ..."
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Cited by 84 (2 self)
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We introduce a natural variant of the (metric uncapacitated) kmedian problem that we call the online median problem. Whereas the kmedian problem involves optimizing the simultaneous placement of k facilities, the online median problem imposes the following additional constraints: the facilities are placed one at a time; a facility cannot be moved once it is placed, and the total number of facilities to be placed, k, is not known in advance. The objective of an online median algorithm is to minimize the competitive ratio, that is, the worstcase ratio of the cost of an online placement to that of an optimal offline placement. Our main result is a lineartime constantcompetitive algorithm for the online median problem. In addition, we present a related, though substantially simpler, lineartime constantfactor approximation algorithm for the (metric uncapacitated) facility location problem. The latter algorithm is similar in spirit to the recent primaldualbased facility location algorithm of Jain and Vazirani, but our approach is more elementary and yields an improved running time.
The Facility Location Problem with General Cost Functions
 Networks
, 2002
"... In this paper we introduce a generalized version of the facility location problem in which the facility cost is a function of the number of clients assigned to the facility. We focus on the case of concave facility cost functions. We observe that this problem can be reduced to the uncapacitated faci ..."
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Cited by 31 (4 self)
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In this paper we introduce a generalized version of the facility location problem in which the facility cost is a function of the number of clients assigned to the facility. We focus on the case of concave facility cost functions. We observe that this problem can be reduced to the uncapacitated facility location problem. We analyze a natural greedy algorithm for this problem and show that its approximation factor is at most 1.861. We also consider several generalizations and variants of this problem.
Gamps: Compressing multi sensor data by grouping and amplitude scaling
 In: ACM SIGMOD. (2009
"... We consider the problem of collectively approximating a set of sensor signals using the least amount of space so that any individual signal can be efficiently reconstructed within a given maximum (L∞) error ε. The problem arises naturally in applications that need to collect large amounts of data fr ..."
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Cited by 19 (0 self)
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We consider the problem of collectively approximating a set of sensor signals using the least amount of space so that any individual signal can be efficiently reconstructed within a given maximum (L∞) error ε. The problem arises naturally in applications that need to collect large amounts of data from multiple concurrent sources, such as sensors, servers and network routers, and archive them over a long period of time for offline data mining. We present GAMPS, a general framework that addresses this problem by combining several novel techniques. First, it dynamically groups multiple signals together so that signals within each group are correlated and can be maximally compressed jointly. Second, it appropriately scales the amplitudes of different signals within a group and compresses them within the maximum allowed reconstruction error bound. Our schemes are polynomial time O(α, β) approximation schemes, meaning that the maximum (L∞) error is at most αε and it uses at most β times the optimal memory. Finally, GAMPS maintains an index so that various queries can be issued directly on compressed data. Our experiments on several realworld sensor datasets show that GAMPS significantly reduces space without compromising the quality of search and query. Categories and Subject Descriptors
The adoption of electronic data interchange: a model and practical tool for managers. Decision Support Systems
, 2000
"... Despite the benefits of standardsbased Electronic Data Interchange (EDI) modes of communication, only a small percentage of organizations have adopted even a single form of EDI. Organizations are often unable to assess the benefits resulting from the adoption of EDI due to the complexity of operati ..."
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Cited by 18 (2 self)
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Despite the benefits of standardsbased Electronic Data Interchange (EDI) modes of communication, only a small percentage of organizations have adopted even a single form of EDI. Organizations are often unable to assess the benefits resulting from the adoption of EDI due to the complexity of operational issues. This paper develops a model and decision support tool for identifying if EDI adoption is cost effective. In contrast to previous research, the model presented allows for the simultaneous adoption of multiple modes of communication. This tool is used to predict the appropriateness of EDI adoption with greater than 85 % accuracy.
Parallelization of the scatter search for the pmedian problem
 Parallel Computing
, 2003
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Parallel Variable Neighborhood Search
, 2004
"... Les textes publiés dans la série des rapports de recherche HEC n’engagent que la responsabilite ́ de leurs auteurs. La publication de ces rapports de recherche bénéficie d’une subvention du Fonds québécois de la recherche sur la nature et les technologies. ..."
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Cited by 1 (0 self)
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Les textes publiés dans la série des rapports de recherche HEC n’engagent que la responsabilite ́ de leurs auteurs. La publication de ces rapports de recherche bénéficie d’une subvention du Fonds québécois de la recherche sur la nature et les technologies.
A biobjective uncapacitated facility location problem
, 1997
"... We consider a biobjective model for uncapacitated facility location where one objective is to maximize the net profit and the other to maximize the profitability of the investment. We first characterize the structure of the model having both a linear and a fractional objective function. In order to ..."
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Cited by 1 (0 self)
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We consider a biobjective model for uncapacitated facility location where one objective is to maximize the net profit and the other to maximize the profitability of the investment. We first characterize the structure of the model having both a linear and a fractional objective function. In order to generate fficient solutions for the model, we develop a heuristic procedure which has computational dvantages over existing methods. A numerical example is presented to illustrate the solution process and computational tests on large scale problems are also provided.
Placement of Nodes in an Adaptive Distributed Multimedia Server
 In Proceedings of the 10th International EuroPar Conference, 2004
"... Partial support of the EC Centre of Excellence programme (No. ICA1CT200070025) and ..."
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Cited by 1 (1 self)
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Partial support of the EC Centre of Excellence programme (No. ICA1CT200070025) and