Improved scheduling algorithms for minsum criteria

Extended abstract
  • Soumen Chakrabarti
  • Cynthia A. Phillips
  • Andreas S. Schulz
  • David B. Shmoys
  • Cliff Stein
  • Joel Wein
Session 16: Algorithms II

DOI: 10.1007/3-540-61440-0_166

Volume 1099 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Chakrabarti S., Phillips C.A., Schulz A.S., Shmoys D.B., Stein C., Wein J. (1996) Improved scheduling algorithms for minsum criteria. In: Meyer F., Monien B. (eds) Automata, Languages and Programming. ICALP 1996. Lecture Notes in Computer Science, vol 1099. Springer, Berlin, Heidelberg

Abstract

We consider the problem of finding near-optimal solutions for a variety of NP-hard scheduling problems for which the objective is to minimize the total weighted completion time. Recent work has led to the development of several techniques that yield constant worst-case bounds in a number of settings. We continue this line of research by providing improved performance guarantees for several of the most basic scheduling models, and by giving the first constant performance guarantee for a number of more realistically constrained scheduling problems. For example, we give an improved performance guarantee for minimizing the total weighted completion time subject to release dates on a single machine, and subject to release dates and/or precedence constraints on identical parallel machines. We also give improved bounds on the power of preemption in scheduling jobs with release dates on parallel machines.

We give improved on-line algorithms for many more realistic scheduling models, including environments with parallelizable jobs, jobs contending for shared resources, tree precedence-constrained jobs, as well as shop scheduling models. In several of these cases, we give the first constant performance guarantee achieved on-line. Finally, one of the consequences of our work is the surprising structural property that there are schedules that simultaneously approximate the optimal makespan and the optimal weighted completion time to within small constants. Not only do such schedules exist, but we can find approximations to them with an on-line algorithm.

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Copyright information

© Springer-Verlag 1996

Authors and Affiliations

  • Soumen Chakrabarti
    • 1
  • Cynthia A. Phillips
    • 2
  • Andreas S. Schulz
    • 3
  • David B. Shmoys
    • 4
  • Cliff Stein
    • 5
  • Joel Wein
    • 6
  1. 1.Computer Science DivisionU. C. Berkeley
  2. 2.Sandia National LabsAlbuquerque
  3. 3.Department of MathematicsTechnical University of BerlinBerlinGermany
  4. 4.School of Operations Research and Industrial EngineeringCornell UniversityIthaca
  5. 5.Department of Computer Science, Sudikoff LaboratoryDartmouth CollegeHanover
  6. 6.Department of Computer SciencePolytechnic UniversityBrooklyn