A NEW HYBRID PRP-MMSIS CONJUGATE GRADIENT METHOD AND ITS APPLICATION IN PORTOFOLIO SELECTION

Authors

DOI:

https://doi.org/10.26740/jram.v5n1.p47-59

Keywords:

Conjugate gradient method, Exact line search, Sufficient descent condition, Global convergence, Portfolio selection

Abstract

In this paper, we propose a new hybrid coefficient of conjugate gradient method (CG) for solving unconstrained optimization model.  The new coefficient is combination of part the MMSIS (Malik et.al, 2020) and PRP (Polak, Ribi'ere \& Polyak, 1969) coefficients.  Under exact line search, the search direction of new method satisfies the sufficient descent condition and based on certain assumption, we establish the global convergence properties.  Using some test functions, numerical results show that the proposed method is more efficient than MMSIS method.  Besides, the new method can be used to solve problem in minimizing portfolio selection risk .

Author Biographies

Sindy Devila, Universitas Indonesia

Department of Mathematics

Maulana Malik, Universitas Indonesia

Department of Mathematics

Wed Giyarti, Universitas Islam Negeri Sunan Kalijaga Yogyakarta

Program Studi Pendidikan Matematika

References

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Published

01-05-21

Issue

Vol. 5 No. 1 (2021): April, JRAM

Section

Algebra
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