Efficient Nonlinear Optimization with Rigorous Models for Large Scale Industrial Chemical Processes

Efficient Nonlinear Optimization with Rigorous Models for Large Scale Industrial Chemical Processes

Large scale nonlinear programming (NLP) has proven to be an effective framework for obtaining profit gains through optimal process design and operations in chemical engineering. While the classical SQP and Interior Point methods have been successfully applied to solve many optimization problems, the...

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Bibliographic Details
Main Author: Zhu, Yu
Other Authors: Laird, Carl
Format: Others
Language:en_US
Published: 2011
Subjects:
nonlinear optimization
air separation
design under uncertainty
parallel algorithm
water network
rigorous model
Online Access:http://hdl.handle.net/1969.1/ETD-TAMU-2011-05-9093

Internet

http://hdl.handle.net/1969.1/ETD-TAMU-2011-05-9093

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