Approximation algorithms for the job interval selection problem and related scheduling problems

J. Chuzhoy*, R. Ostrovsky, Y. Rabani

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

39 Scopus citations

Abstract

In this paper we consider the job interval selection problem (JISP), a simple scheduling model with a rich history and numerous applications. Special cases of this problem include the so-called real-time scheduling problem (also known as the throughput maximization problem) in single and multiple machine environments. In these special cases we have to maximize the number of jobs scheduled between their release date and deadline (preemption is not allowed). Even the single machine case is NP-hard. The unrelated machines case, as well as other special cases of JISP, are MAX SNP-hard. A simple greedy algorithm gives a 2-approximation for JISP. Despite many efforts, this was the best approximation guarantee known, even for throughput maximization on a single machine. In this paper, we break this barrier and show an approximation guarantee of less than 1.582 for arbitrary instances of JISP. For some special cases, we show better results. Our methods can be used to give improved bounds for some related resource allocation problems that were considered recently in the literature.

Original languageAmerican English
Pages (from-to)348-356
Number of pages9
JournalAnnual Symposium on Foundations of Computer Science - Proceedings
DOIs
StatePublished - 2001
Externally publishedYes
Event42nd Annual Symposium on Foundations of Computer Science - Las Vegas, NV, United States
Duration: 14 Oct 200117 Oct 2001

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