Annals of Operations Research

, Volume 116, Issue 1, pp 113–126

Redefining Event Variables for Efficient Modeling of Continuous-Time Batch Processing

  • Siqun Wang
  • Monique Guignard
Article

DOI: 10.1023/A:1021372029962

Cite this article as:
Wang, S. & Guignard, M. Annals of Operations Research (2002) 116: 113. doi:10.1023/A:1021372029962

Abstract

We define events so as to reduce the number of events and decision variables needed for modeling batch-scheduling problems such as described in [15]. We propose a new MILP formulation based on this concept, defining non-uniform time periods as needed and decision variables that are not time-indexed. It can handle complicated multi-product/multi-stage machine processes, with production lines merging and diverging, and with minimum and maximum batch sizes. We compare it with earlier models and show that it can solve problems with small to medium demands relative to batch sizes in reasonable computer times.

continuous-time model batch event scheduling makespan integer programming 

Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • Siqun Wang
    • 1
  • Monique Guignard
    • 1
  1. 1.500 JMHH, Department of OPIM, The Wharton SchoolUniversity of PennsylvaniaPhiladelphiaUSA

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