کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5776138 | 1631963 | 2018 | 24 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A Tikhonov regularized penalty function approach for solving polylinear programming problems
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
ریاضیات کاربردی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
This paper suggests a new regularized penalty method for poly-linear functions. Until our knowledge it is the first time that a regularization approach solution for poly-linear programming is reported in the literature. We propose a penalty function depending on two parameters μ and δ for ensuring the strong convexity and the existence of a unique solution involving equality and inequality constraints. We prove that if the penalty parameter μ
tends to zero then the solution of the original problem converges to a unique solution with the minimal weighted norm. We introduce a recurrent procedure based on the projection-gradient method for finding the extremal points and we also prove the convergence of the method. We develop an example for game theory and additional example for portfolio optimization employing the proposed regularization method for Markov chains involving the definition of a poly-linear function.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Computational and Applied Mathematics - Volume 328, 15 January 2018, Pages 267-286
Journal: Journal of Computational and Applied Mathematics - Volume 328, 15 January 2018, Pages 267-286
نویسندگان
Julio B. Clempner, Alexander S. Poznyak,