An Efficient Limited Memory Multi-Step Quasi-Newton Method

Autor:	Issam A. R. Moghrabi, Basim A. Hassan
Jazyk:	angličtina
Rok vydání:	2024
Předmět:	quasi-Newton methods multi-step methods unconstrained optimization limited memory methods Mathematics QA1-939
Zdroj:	Mathematics, Vol 12, Iss 5, p 768 (2024)
Druh dokumentu:	article
ISSN:	12050768 2227-7390
DOI:	10.3390/math12050768
Popis:	This paper is dedicated to the development of a novel class of quasi-Newton techniques tailored to address computational challenges posed by memory constraints. Such methodologies are commonly referred to as “limited” memory methods. The method proposed herein showcases adaptability by introducing a customizable memory parameter governing the retention of historical data in constructing the Hessian estimate matrix at each iterative stage. The search directions generated through this novel approach are derived from a modified version closely resembling the full memory multi-step BFGS update, incorporating limited memory computation for a singular term to approximate matrix–vector multiplication. Results from numerical experiments, exploring various parameter configurations, substantiate the enhanced efficiency of the proposed algorithm within the realm of limited memory quasi-Newton methodologies category.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/5d61518c460549e69b7e4510af48bd6e Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF Plný text ve formátu HTML
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