Nonlinear Optimization of Chemical Processes

Large scale nonlinear programming (NLP) has proven to be an e ective framework for obtaining pro t gains through optimal process design and operations in chemical engineering. The focus of both academia and industry on larger and more complicated problems requires further development of numerical algorithms which can provide improved computational e ciency. The primary purpose of this book is to develop e ective problem formulations and an advanced numerical algorithms for e cient solution of these challenging problems. In this book, we develop an advanced parallel solution strategy for nonlinear programming problems. The e ectiveness of this modern tool is demonstrated on a wide range of chemical problem classes including air separation unit, water network, and heat-integrated distillation columns.

Autorentext

Yu Zhu, development specialist at Praxair Inc, focuses on process design, control and optimization of large scale industrial processes. He received both his Ph.D. in Chemical Engineering and M.Eng. in Industrial Engineering at Texas A&M University, USA, as well as M.S. and B.S. of Control Science and Engineering at Zhejiang University, China.

Klappentext

Large scale nonlinear programming (NLP) has proven to be an e ective framework for obtaining pröt gains through optimal process design and operations in chemical engineering. The focus of both academia and industry on larger and more complicated problems requires further development of numerical algorithms which can provide improved computational e ciency. The primary purpose of this book is to develop e ective problem formulations and an advanced numerical algorithms for e cient solution of these challenging problems. In this book, we develop an advanced parallel solution strategy for nonlinear programming problems. The e ectiveness of this modern tool is demonstrated on a wide range of chemical problem classes including air separation unit, water network, and heat-integrated distillation columns.