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General Information
    • ISSN: 2010-3697  (Online)
    • Abbreviated Title: Int. J. Model. Optim.
    • Frequency: Bimonthly
    • DOI: 10.7763/IJMO
    • Editor-in-Chief: Prof. Adrian Olaru
    • Executive Editor: Ms.Yoyo Y. Zhou
    • Abstracting/ Indexing: ProQuest, Crossref, Electronic Journals Library, Google Scholar, EI (INSPEC, IET), EBSCO, etc.
    • E-mail ijmo@iacsitp.com
Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
I'm happy to take on the position of editor in chief of IJMO. It's a journal that shows promise of becoming a recognized journal in the area of modelling and optimization. I'll work together with the editors to help it progress.
IJMO 2018 Vol.8(3): 131-137 ISSN: 2010-3697
DOI: 10.7763/IJMO.2018.V8.637

Sub-Direction Parallel Search Quasi-Newton Algorithm

Wang Bao and Wang Yanxin
Abstract—Advantages and disadvantages in a sequence of unconstrained optimization method are basically compared. The original constrained problem is replaced by a sequence of unconstrained sub-problems through the augmented Lagrangian multiplier method. The unconstrained sub-problems are solved by BFGS method and the sub-direction parallel search quasi-Newton algorithm. Efficiency of this method is compared. The results of numerical tests show that the calculation time of the sub-direction parallel search quasi-Newton algorithm is short and it can solve engineering optimization problems completely.

Index Terms—Quasi-Newton equation, taylor series, global convergence, iteration formula.

The authors are with Ningbo University of Technology, School of Science, China (e-mail: 864787886@ qq.com).


Cite: Wang Bao and Wang Yanxin, "Sub-Direction Parallel Search Quasi-Newton Algorithm," International Journal of Modeling and Optimization vol. 8, no. 3, pp. 131-137, 2018.

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