Modeling and Managing Uncertainty in Process Planning and Scheduling

Marianthi Ierapetritou () and Zukui Li ()
Additional contact information
Marianthi Ierapetritou: Rutgers University
Zukui Li: Rutgers University

A chapter in Optimization and Logistics Challenges in the Enterprise, 2009, pp 97-144 from Springer

Abstract: Summary 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.

Keywords: Schedule Problem; Uncertain Parameter; Mixed Integer Linear Programming; Linear Programming Relaxation; Periodic Schedule (search for similar items in EconPapers)
Date: 2009
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-0-387-88617-6_3

Ordering information: This item can be ordered from
http://www.springer.com/9780387886176

DOI: 10.1007/978-0-387-88617-6_3

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().