Advertisement

Robust Scheduling Problems

  • Panos Kouvelis
  • Gang Yu
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 14)

Abstract

In Example 7 of Chapter 2 we introduced the notion of robust scheduling. Schedulers confronted with significant processing time uncertainty often discover that a schedule which is optimal with respect to a deterministic or stochastic scheduling model yields quite poor performance when evaluated relative to the actual processing times. In these environments, the notion of schedule robustness, i.e., determining the schedule with the best worst-case performance compared to the corresponding optimal solution over all potential realizations of job processing times, is a more appropriate guide to schedule selection. The benefits of robust decision making in a scheduling context have been clearly illustrated through an example in Chapter 1 (Section 1.1 and Section 1.2).

Keywords

Processing Time Schedule Problem Optimal Makespan Processing Time Interval Dominance Property 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    Carpaneto, G., S. Martello and P. Toth (1988), “Algorithms and Codes for the Assignment Problem,” Annals or Operations Research, 7, 200–218.MathSciNetGoogle Scholar
  2. [2]
    ; Daniels, R.L. and P. Kouvelis (1992), “Robust Scheduling to Hedge Against Processing Time Uncertainty in Single-Stage Production,” Working paper, Fuqua School of Business, Duke University.Google Scholar
  3. [3]
    Daniels, R.L. and P. Kouvelis (1995), “Robust Scheduling to Hedge Against Processing Time Uncertainty in Single-Stage Production,” Management Science, 41, 2, 363–376.zbMATHCrossRefGoogle Scholar
  4. [4]
    Glover, F. (1975), “Surrogate Constraint Duality in Mathematical Programming,” Operations Research, 23, 434–453.MathSciNetzbMATHCrossRefGoogle Scholar
  5. [5]
    Johnson, S.M. (1954), “Optimal Two- and Three-Stage Production Schedules with Setup Times Included,” Naval Research Logistics Quarterly, 1, 61–68.CrossRefGoogle Scholar
  6. [6]
    Kouvelis, P., R.L. Daniels and G. Vairaktarakis (1996), “Robust Scheduling of a Two-Machine Flow Shop with Uncertain Processing Times,” Working Paper, Fuqua School of Business, Duke University (to appear in Naval Research Logistics). Google Scholar
  7. [7]
    Lawler, E.L. (1976), Combinatorial Optimization: Networks and Matroids, Holt, Rinehart and Winston, New York.zbMATHGoogle Scholar
  8. [8]
    Yu, G. (1993), “On the Robust One-Machine Scheduling Problem,” Working Paper, Department of MSIS, Graduate School of Business, The University of Texas at Austin.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 1997

Authors and Affiliations

  • Panos Kouvelis
    • 1
  • Gang Yu
    • 2
  1. 1.Olin School of BusinessWashington University at St. LouisSt. LouisUSA
  2. 2.Center for Cybernetic StudiesThe University of TexasAustinUSA

Personalised recommendations