### Abstract

We consider the problem of off-line throughput maximization for job scheduling on one or more machines, where each job has a release time, a deadline and a profit. Most of the versions of the problem discussed here were already treated by Bar-Noy et al. [3]. Our main contribution is to provide algorithms that do not use linear programming, are simple and much faster than the corresponding ones proposed in [3], while either having the same quality of approximation or improving it. More precisely, compared to the results of in Bar-Noy et al. [3], our pseudo-polynomial algorithm for multiple unrelated machines and all of our strongly-polynomial algorithms have better performance ratios, all of our algorithms run much faster, are combinatorial in nature and avoid linear programming. Finally, we show that algorithms with better performance ratios than 2 are possible if the stretch factors of the jobs are bounded; a straightforward consequence of this result is an improvement of the ratio of an optimal solution of the integer programming formulation of the JISP2 problem (see [13]) to its linear programming relaxation.

Original language | English (US) |
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Title of host publication | Proceedings of the 32nd Annual ACM Symposium on Theory of Computing, STOC 2000 |

Pages | 680-687 |

Number of pages | 8 |

DOIs | |

State | Published - Dec 1 2000 |

Event | 32nd Annual ACM Symposium on Theory of Computing, STOC 2000 - Portland, OR, United States Duration: May 21 2000 → May 23 2000 |

### Publication series

Name | Proceedings of the Annual ACM Symposium on Theory of Computing |
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ISSN (Print) | 0737-8017 |

### Conference

Conference | 32nd Annual ACM Symposium on Theory of Computing, STOC 2000 |
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Country | United States |

City | Portland, OR |

Period | 5/21/00 → 5/23/00 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Software

### Cite this

*Proceedings of the 32nd Annual ACM Symposium on Theory of Computing, STOC 2000*(pp. 680-687). (Proceedings of the Annual ACM Symposium on Theory of Computing). https://doi.org/10.1145/335305.335401

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*Proceedings of the 32nd Annual ACM Symposium on Theory of Computing, STOC 2000.*Proceedings of the Annual ACM Symposium on Theory of Computing, pp. 680-687, 32nd Annual ACM Symposium on Theory of Computing, STOC 2000, Portland, OR, United States, 5/21/00. https://doi.org/10.1145/335305.335401

**Improvements in throughout maximization for real-time scheduling.** / Berman, Piotr; Dasgupta, Bhaskar.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Improvements in throughout maximization for real-time scheduling

AU - Berman, Piotr

AU - Dasgupta, Bhaskar

PY - 2000/12/1

Y1 - 2000/12/1

N2 - We consider the problem of off-line throughput maximization for job scheduling on one or more machines, where each job has a release time, a deadline and a profit. Most of the versions of the problem discussed here were already treated by Bar-Noy et al. [3]. Our main contribution is to provide algorithms that do not use linear programming, are simple and much faster than the corresponding ones proposed in [3], while either having the same quality of approximation or improving it. More precisely, compared to the results of in Bar-Noy et al. [3], our pseudo-polynomial algorithm for multiple unrelated machines and all of our strongly-polynomial algorithms have better performance ratios, all of our algorithms run much faster, are combinatorial in nature and avoid linear programming. Finally, we show that algorithms with better performance ratios than 2 are possible if the stretch factors of the jobs are bounded; a straightforward consequence of this result is an improvement of the ratio of an optimal solution of the integer programming formulation of the JISP2 problem (see [13]) to its linear programming relaxation.

AB - We consider the problem of off-line throughput maximization for job scheduling on one or more machines, where each job has a release time, a deadline and a profit. Most of the versions of the problem discussed here were already treated by Bar-Noy et al. [3]. Our main contribution is to provide algorithms that do not use linear programming, are simple and much faster than the corresponding ones proposed in [3], while either having the same quality of approximation or improving it. More precisely, compared to the results of in Bar-Noy et al. [3], our pseudo-polynomial algorithm for multiple unrelated machines and all of our strongly-polynomial algorithms have better performance ratios, all of our algorithms run much faster, are combinatorial in nature and avoid linear programming. Finally, we show that algorithms with better performance ratios than 2 are possible if the stretch factors of the jobs are bounded; a straightforward consequence of this result is an improvement of the ratio of an optimal solution of the integer programming formulation of the JISP2 problem (see [13]) to its linear programming relaxation.

UR - http://www.scopus.com/inward/record.url?scp=0033722340&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0033722340&partnerID=8YFLogxK

U2 - 10.1145/335305.335401

DO - 10.1145/335305.335401

M3 - Conference contribution

AN - SCOPUS:0033722340

SN - 1581131844

SN - 9781581131840

T3 - Proceedings of the Annual ACM Symposium on Theory of Computing

SP - 680

EP - 687

BT - Proceedings of the 32nd Annual ACM Symposium on Theory of Computing, STOC 2000

ER -