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Modeling and Managing Uncertainty in Process Planning and Scheduling

In: Optimization and Logistics Challenges in the Enterprise

Author

Listed:
  • Marianthi Ierapetritou

    (Rutgers University)

  • Zukui Li

    (Rutgers University)

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.

Suggested Citation

  • Marianthi Ierapetritou & Zukui Li, 2009. "Modeling and Managing Uncertainty in Process Planning and Scheduling," Springer Optimization and Its Applications, in: Wanpracha Chaovalitwongse & Kevin C. Furman & Panos M. Pardalos (ed.), Optimization and Logistics Challenges in the Enterprise, pages 97-144, Springer.
  • Handle: RePEc:spr:spochp:978-0-387-88617-6_3
    DOI: 10.1007/978-0-387-88617-6_3
    as

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