Modeling and managing uncertainty in process planning and scheduling

Marianthi Ierapetritou, Zukui Li

Research output: Chapter in Book/Report/Conference proceedingChapter

8 Scopus citations


Uncertainty appears in all the different levels of the industry from the detailed process description to multisite manufacturing. The successful utilization of process models relies heavily on the ability to handle system variability. Thus modeling and managing uncertainty in process planning and scheduling has received a lot of attention in the open literature in recent years from chemical engineering and operations research communities. The purpose of this chapter is to review the main methodologies that have been developed to address the problem of uncertainty in production planning and scheduling as well as to identify the main challenges in this area. The uncertainties in process operations are first analyzed, and the different mathematical approaches that exist to describe process uncertainties are classified. Based on the different descriptions for the uncertainties, alternative planning and scheduling approaches and relevant optimization models are reviewed and discussed. Further research challenges in the field of planning and scheduling under uncertainty are identified and some new ideas are discussed.

Original languageEnglish (US)
Title of host publicationSpringer Optimization and Its Applications
PublisherSpringer International Publishing
Number of pages48
StatePublished - 2009

Publication series

NameSpringer Optimization and Its Applications
ISSN (Print)1931-6828
ISSN (Electronic)1931-6836

All Science Journal Classification (ASJC) codes

  • Control and Optimization


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