Two-Phase-SQP Method with Higher-Order Convergence Property

We propose a two-phase-SQP (Sequential Quadratic Programming) algorithm for equality-constrained optimization problem. In this paper, an iteration process is developed, and at each iteration, two quadratic sub-problems are solved. It is proved that, under some suitable assumptions and without comput...

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Vydáno v:Journal of the Operations Research Society of China (Internet) Ročník 4; číslo 3; s. 385 - 396
Hlavní autoři: Chakraborty, Suvra Kanti, Panda, Geetanjali
Médium: Journal Article
Jazyk:angličtina
Vydáno: Beijing Operations Research Society of China 01.09.2016
Springer Nature B.V
Témata:
Algorithms
Convergence
Iterative methods
Lagrange multiplier
Management Science
Mathematics
Mathematics and Statistics
Methods
Operations Research
Optimization
Quadratic programming
Cubic-order convergence
90C30
90C55
Constrained optimization
Newton-SQP method
ISSN:2194-668X, 2194-6698
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Shrnutí:We propose a two-phase-SQP (Sequential Quadratic Programming) algorithm for equality-constrained optimization problem. In this paper, an iteration process is developed, and at each iteration, two quadratic sub-problems are solved. It is proved that, under some suitable assumptions and without computing further higher-order derivatives, this iteration process achieves higher-order local convergence property in comparison to Newton-SQP scheme. Theoretical advantage and a note on l 1 merit function associated to the method are provided.
Bibliografie:ObjectType-Article-1
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ISSN:2194-668X
2194-6698
DOI:10.1007/s40305-016-0122-6