Skip to main content

Techniques for Scheduling with Rejection

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1461))

Abstract

We consider the general problem of scheduling a set of jobs where we may choose not to schedule certain jobs, and thereby incur a penalty for each rejected job. More specifically, we focus on choosing a set of jobs to reject and constructing a schedule for the remaining jobs so as to optimize the sum of the weighted completion times of the jobs scheduled plus the sum of the penalties of the jobs rejected.

We give several techniques for designing scheduling algorithms under this criterion. Many of these techniques show how to reduce a problem with rejection to a (potentially more complex) scheduling problem without rejection. Some of the reductions are based on general properties of certain kinds of linear-programming relaxations of optimization problems, and therefore are applicable to problems outside of scheduling; we demonstrate this by giving an approximation algorithm for a variant of the facility-location problem.

In the last section of the paper we consider a different notion of rejection in the context of scheduling: scheduling jobs with due dates so as to maximize the number of jobs that complete by their due dates, or equivalently to minimize the number of jobs that do not complete by their due date and that thus can be considered “rejected.” We investigate the approximability of a simple version of this problem, giving approximation algorithms and characterizing integrality gaps of a class of linear-programming relaxations.

Research supported by NSF Contract MIP-9612632.

Research supported in part by ARPA contract N00014-95-1-1246 and NSF contract CCR-9624239, as well as grants from the Alfred P. Sloane and David and Lucille Packard foundations.

Research partially supported by NSF Award CCR-9308701 and NSF Career Award CCR-9624828.

Research partially supported by NSF Grant CCR-9626831.

Research partially supported by NSF Grant CCR-9626831 and a grant from the New York State Science and Technology Foundation, through its Center for Advanced Technology in Telecommunications.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Y. Bartal, S. Leonardi, A. Marchetti-Spaccamela, J. Sgall, and L. Stougie. Multiprocessor scheduling with rejection. In Proc. 7th SODA, 95–103, 1996.

    Google Scholar 

  2. C. Chekuri, R. Motwani, B. Natarajan, and C. Stein. Approximation techniques for average completion time scheduling. In Proc. 8th SODA, 609–618, 1997.

    Google Scholar 

  3. F. A. Chudak. Improved approximation algorithms for uncapacitated facility location. In Proc. 6th IPCO 1998. To appear.

    Google Scholar 

  4. M.R. Garey and D.S. Johnson. Computers and Intractability: A Guide to the Theory of NP-Completeness. W.H. Freeman and Company, New York, 1979.

    MATH  Google Scholar 

  5. M. Goemans. Improved approximation algorithms for scheduling with release dates. In Proc. 8th SODA, 591–598, 1997.

    Google Scholar 

  6. R.L. Graham, E.L. Lawler, J.K. Lenstra, and A.H.G. Rinnooy Kan. Optimization and approximation in deterministic sequencing and scheduling: a survey. Annals of Discrete Mathematics, 5:287–326, 1979.

    Article  MATH  MathSciNet  Google Scholar 

  7. S. Guha and S. Khuller. Greedy strikes back: Improved facility location algorithms. In Proc. 9th SODA, 1998.

    Google Scholar 

  8. L. A. Hall, A. S. Schulz, D. B. Shmoys, and J. Wein. Scheduling tominimize average completion time: Off-line and on-line approximation algorithms. Mathematics of Operations Research, (3):513–544, August 1997.

    MathSciNet  Google Scholar 

  9. E. L. Lawler. Scheduling a single machine to minimize the number of late jobs. Preprint, Computer Science Division, Univ. of California, Berkeley, 1982.

    Google Scholar 

  10. E. L. Lawler and J. M. Moore. A functional equation and its application to resource allocation and sequencing problems. In Manag. Sci., volume 16, 77–84, 1969.

    MATH  Google Scholar 

  11. E. L. Lawler and D. B. Shmoys. Weighted number of late jobs (preliminary version). To appear in: J.K. Lenstra and D.B. Shmoys (eds.) Scheduling, Wiley.

    Google Scholar 

  12. Maxwell. Personal communication. 1996.

    Google Scholar 

  13. I. M. Ovacik and R. Uzsoy. DecompositionMethods for Complex Factory Scheduling Problems. Kluwer Academic Publishers, 1997.

    Google Scholar 

  14. C. Phillips, C. Stein, and J. Wein. Scheduling jobs that arrive over time. In Proc. of 4th WADS, LNCS, 955, 86–97, Berlin, 1995. Springer-Verlag. To appear in Mathematical Programming B.

    Google Scholar 

  15. M. H. Rothkopf. Scheduling independent tasks on parallel processors. In Manag. Sci., volume 12, 437–447, 1966.

    Article  MathSciNet  Google Scholar 

  16. A. S. Schulz and M. Skutella. Random-based scheduling: New approximations and LP lower bounds. In J. Rolim, editor, Randomization and Approximation Techniques in Computer Science, LNCS, 955, 119–133. Springer, Berlin, 1997.

    Google Scholar 

  17. A. S. Schulz and M. Skutella. Scheduling-LPs bear probabilities: Randomized approximations for min-sum criteria. In R. Burkard and G. Woeginger, editors, Algorithms — ESA’97, LNCS, 1284, 416–429. Springer, Berlin, 1997.

    Google Scholar 

  18. D. B. Shmoys, É. Tardos, and K. Aardal. Approximation algorithms for facility location problems. In Proc. of the 29th ACM STOC, 265–274, 1997.

    Google Scholar 

  19. W.E. Smith. Various optimizers for single-stage production. Naval Research Logistics Quarterly, 3:59–66, 1956.

    Article  MathSciNet  Google Scholar 

  20. M. E. Dyer and L. A. Wolsey. Formulating the single machine sequencing problem with release dates as a mixed integer program. In Discrete Applied Mathematics, 26, 255–270, 1990.

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1998 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Engels, D.W., Karger, D.R., Kolliopoulos, S.G., Sengupta, S., Uma, R.N., Wein, J. (1998). Techniques for Scheduling with Rejection. In: Bilardi, G., Italiano, G.F., Pietracaprina, A., Pucci, G. (eds) Algorithms — ESA’ 98. ESA 1998. Lecture Notes in Computer Science, vol 1461. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-68530-8_41

Download citation

  • DOI: https://doi.org/10.1007/3-540-68530-8_41

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64848-2

  • Online ISBN: 978-3-540-68530-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics