Challenges in the application of mathematical programming in the enterprise-wide optimization of process industries

被引:0
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作者
Ignacio E. Grossmann
机构
[1] Carnegie Mellon University,Center for Advanced Process Decision
关键词
mathematical programming; enterprise-wide optimization; process industries; modeling; planning; scheduling; real-time optimization; control; mixed-integer linear and nonlinear optimization methods; decomposition methods; stochastic programming;
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摘要
Enterprise-wide optimization (EWO) 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 supply, manufacturing and distribution activities of a company to reduce costs, inventories and environmental impact, and to maximize profits and responsiveness. Major operational items include planning, scheduling, real-time optimization and control. We provide an overview of EWO in terms of a mathematical programming framework. We first provide a brief overview of mathematical programming techniques (mixed-integer linear and nonlinear optimization methods), as well as decomposition methods, stochastic programming and modeling systems. We then address some of the major challenges involved in the modeling and solution of these problems. Finally, we describe several applications to show the potential of this area.
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页码:555 / 573
页数:18
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