Space constrained optimization problems arise in a variety of applications, ranging from databases to ubiquitous computing. Typically, these problems involve selecting a set of items of interest, subject to a space constraint. We show that in many important applications, one faces variants of this basic problem, in which the individual items are sets themselves, and each set is associated with a benefit value. Since there are no known approximation algorithms for these problems, we explore the use of greedy and randomized techniques. We present a detailed performance and theoretical evaluation of the algorithms, highlighting the efficiency of the proposed solutions.

On Space Constrained Set Selection Problems

Palpanas, Themistoklis;
2008

Abstract

Space constrained optimization problems arise in a variety of applications, ranging from databases to ubiquitous computing. Typically, these problems involve selecting a set of items of interest, subject to a space constraint. We show that in many important applications, one faces variants of this basic problem, in which the individual items are sets themselves, and each set is associated with a benefit value. Since there are no known approximation algorithms for these problems, we explore the use of greedy and randomized techniques. We present a detailed performance and theoretical evaluation of the algorithms, highlighting the efficiency of the proposed solutions.
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Palpanas, Themistoklis; N., Koudas; A., Mendelzon
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11572/69148
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