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Challenges in Enterprise Wide Optimization for the Process Industries

  • Ignacio E. Grossmann
  • Kevin C. Furman
Chapter
Part of the Springer Optimization and Its Applications book series (SOIA, volume 30)

Summary

Enterprisewide optimization (EWO) is a new emerging area that lies at the interface of chemical engineering and operations research, and has become a major goal in the process industries due to the increasing pressures for remaining competitive in the global marketplace. EWO involves optimizing the operations of supply, manufacturing, and distribution activities of a company to reduce costs and inventories. A major focus in EWO is the optimal operation of manufacturing facilities, which often requires the use of nonlinear process models. Major operational items include planning, scheduling, real-time optimization, and inventory control. This chapter provides an overview of major challenges in the development of deterministic and stochastic linear/nonlinear optimization models and algorithms for the optimization of entire supply chains that are involved in EWO problems. We specifically review three major challenges: (a) modeling of planning and scheduling, (b) multiscale optimization, and (c) handling of uncertainties. Finally, we also discuss briefly the algorithmic methods and tools that are required for tackling these problems, and we conclude with future research needs in this area.

Keywords

Supply Chain Schedule Problem Stochastic Programming MILP Model Batch Plant 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

Acknowledgements

The authors would like to acknowledge financial support from the Pennsylvania Infrastructure Alliance, the Center for Advanced Process Decision making at Carnegie Mellon University, ExxonMobil Corporation, and from DIMACS at Rutgers University.

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Copyright information

© Springer-Verlag US 2009

Authors and Affiliations

  1. 1.Department of Chemical EngineeringCarnegie Mellon UniversityPittsburgh
  2. 2.Corporate Strategic Research ExxonMobil Research & EngineeringAnnandale

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