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Title: A New Algorithm Based on rSQP and AD
Authors: Li, Jin
Tan, Yuejin
Liao, Liangcai
Issue Date: 9-Mar-2007
Abstract: An efficient optimization algorithm based on reduced sequential quadratic programming (rSQP) and automatic differentiation (AD) is presented in this paper. With the characteristics of sparseness, relatively low degrees of freedom and equality constraints utilized, the nonlinear programming problem was solved by improved rSQP solver. In the solving process, AD technology was used to obtain accurate gradient information. The numerical results show that the combined algorithm, which is suitable for large-scale process optimization problems, can calculate more efficiently than rSQP itself.
Type: Article
Appears in Collections:2005 International Conference on Industrial Electronics and Control Applications (FIEE)

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