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OR Spectrum

, Volume 24, Issue 4, pp 467–495 | Cite as

Makespan estimation and order acceptance in batch process industries when processing times are uncertain

  • Cristina V. Ivanescu
  • Jan C. Fransoo
  • J.Will M. Bertrand
Special Issue Paper

Abstract.

Batch process industries are characterized by complex precedence relationships between operations, which renders the estimation of an acceptable workload very difficult. A detailed schedule based model can be used for this purpose, but for large problems this may require a prohibitive large amount of computation time. We propose a regression based model to estimate the makespan of a set of jobs. We extend earlier work based on deterministic processing times by considering Erlang-distributed processing times in our model. This regression-based model is used to support customer order acceptance. Three order acceptance policies are compared by means of simulation experiments: a scheduling policy, a workload policy and a regression policy. The results indicate that the performance of the regression policy can compete with the performance of the scheduling policy in situations with high variety in the job mix and high uncertainty in the processing times.

Key words: Batch process industries – Regression analysis – Order acceptance 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Cristina V. Ivanescu
    • 1
  • Jan C. Fransoo
    • 1
  • J.Will M. Bertrand
    • 1
  1. 1.Department of Technology Management, Technische Universiteit Eindhoven, P.O. Box 513, 5600 MB Eindhoven, The Netherlands (e-mail: {c.v.ivanescu,j.c.fransoo,j.w.m.bertrand}@tm.tue.nl) NL

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