An efficient interior-point algorithm with new non-monotone line search filter method for nonlinear constrained programming

An efficient primal-dual interior-point algorithm using a new non-monotone line search filter method is presented for nonlinear constrained programming, which is widely applied in engineering optimization. The new non-monotone line search technique is introduced to lead to relaxed step acceptance co...

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Vydáno v:Engineering optimization Ročník 49; číslo 2; s. 290 - 310
Hlavní autoři: Wang, Liwei, Liu, Xinggao, Zhang, Zeyin
Médium: Journal Article
Jazyk:angličtina
Vydáno: Abingdon Taylor & Francis 01.02.2017
Taylor & Francis Ltd
Témata:
Algorithms
Constraints
Convergence
filter
interior-point
line search
non-monotone
Nonlinear constrained programming
Nonlinearity
Optimization
Programming
Searching
Upper bounds
ISSN:0305-215X, 1029-0273
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Shrnutí:An efficient primal-dual interior-point algorithm using a new non-monotone line search filter method is presented for nonlinear constrained programming, which is widely applied in engineering optimization. The new non-monotone line search technique is introduced to lead to relaxed step acceptance conditions and improved convergence performance. It can also avoid the choice of the upper bound on the memory, which brings obvious disadvantages to traditional techniques. Under mild assumptions, the global convergence of the new non-monotone line search filter method is analysed, and fast local convergence is ensured by second order corrections. The proposed algorithm is applied to the classical alkylation process optimization problem and the results illustrate its effectiveness. Some comprehensive comparisons to existing methods are also presented.
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ISSN:0305-215X
1029-0273
DOI:10.1080/0305215X.2016.1176828