An optimal choice Dai-Liao conjugate gradient algorithm for unconstrained optimization and portfolio selection-Reference-Cited by-同舟云学术

An optimal choice Dai-Liao conjugate gradient algorithm for unconstrained optimization and portfolio selection

Published:2024 Issue:1 Volume:9 Page:642-664
ISSN:2473-6988
Container-title:AIMS Mathematics
language:
Short-container-title:MATH

Author:

Sabi'u Jamilu¹,Sulaiman Ibrahim Mohammed²³,Kaelo P.⁴,Malik Maulana⁵,Kamaruddin Saadi Ahmad²

Affiliation:

1. Department of Mathematics, Yusuf Maitama Sule University Kano, Nigeria

2. Institute of Strategic Industrial Decision Modelling, School of Quantitative Sciences, Universiti Utara Malaysia, Sintok 06010, Malaysia

3. Faculty of Education and Arts, Sohar University, Sohar 311, Oman

4. Department of Mathematics, University of Botswana, Private Bag UB00704, Gaborone, Botswana

5. Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok 16424, Indonesia

Abstract

<abstract><p>In this research, we propose an optimal choice for the non-negative constant in the Dai-Liao conjugate gradient formula based on the prominent Barzilai-Borwein approach by leveraging the nice features of the Frobenius matrix norm. The global convergence of the new modification is demonstrated using some basic assumptions. Numerical comparisons with similar algorithms show that the new approach is reliable in terms of the number of iterations, computing time, and function evaluations for unconstrained minimization, portfolio selection and image restoration problems.</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

General Mathematics

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