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Main Authors: Sahu, Manish Kumar, Pattanaik, Suvendu Ranjan, Panda, Santosh Kumar
Format: Preprint
Published: 2022
Subjects:
Online Access:https://arxiv.org/abs/2204.11508
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author Sahu, Manish Kumar
Pattanaik, Suvendu Ranjan
Panda, Santosh Kumar
author_facet Sahu, Manish Kumar
Pattanaik, Suvendu Ranjan
Panda, Santosh Kumar
contents The modified BFGS optimization algorithm is generally used when the objective function is non-convex. In this method, one has to move in a specific direction such that the value of the objective function reduces. Therefore, the different inexact line search or exact line search plays an important role in optimization. Here, we have studied Modified BFGS with different inexact line searches methods and compared them in some test problems. Numerical results show that MBFGS with Armijo line search methods is efficient for solving non-convex non-linear unconstrained optimization problems.
format Preprint
id arxiv_https___arxiv_org_abs_2204_11508
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle The Performance of MBFGS with Different Inexact Line Search Rule
Sahu, Manish Kumar
Pattanaik, Suvendu Ranjan
Panda, Santosh Kumar
Optimization and Control
65K10, 90C53
The modified BFGS optimization algorithm is generally used when the objective function is non-convex. In this method, one has to move in a specific direction such that the value of the objective function reduces. Therefore, the different inexact line search or exact line search plays an important role in optimization. Here, we have studied Modified BFGS with different inexact line searches methods and compared them in some test problems. Numerical results show that MBFGS with Armijo line search methods is efficient for solving non-convex non-linear unconstrained optimization problems.
title The Performance of MBFGS with Different Inexact Line Search Rule
topic Optimization and Control
65K10, 90C53
url https://arxiv.org/abs/2204.11508