A New Algorithm Based on rSQP and AD

A New Algorithm Based on rSQP and AD

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 w...

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Библиографические подробности
Главный автор: Li, Jin (author)
Другие авторы: Tan, Yuejin (author), Liao, Liangcai (author)
Формат: article
Язык:eng
Опубликовано: 2007
Предметы:
ALGORITMOS
OPTIMIZACIÓN
ALGORITHMS
OPTIMIZATION
Online-ссылка:http://bibdigital.epn.edu.ec/handle/15000/9322
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Итог: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.

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