Modified spectral conjugate gradient iterative scheme for unconstrained optimization problems with application on COVID-19 model

In this work, a new class of spectral conjugate gradient (CG) method is proposed for solving unconstrained optimization models. The search direction of the new method uses the ZPRP and JYJLL CG coefficients. The search direction satisfies the descent condition independent of the line search. The global convergence properties of the proposed method under the strong Wolfe line search are proved with some certain assumptions. Based on some test functions, numerical experiments are presented to show the proposed method's efficiency compared with other existing methods. The application of the proposed method for solving regression models of COVID-19 is provided. Mathematics subject classification: 65K10, 90C52, 90C26. Copyright © 2022 Novkaniza, Malik, Sulaiman and Aldila.

Measurement of Relative Efficiency Levels of Southeast Asian Countries in Dealing with the Covid-19 Pandemic Over One Year

Introduction: Handling the COVID-19 outbreak is one of the most novelties modern work is facing by many countries today. Massive outbreak needs countries efficacy and talent in creating new approaches. These approaches need to prevent the spread of the outbreak and increase the citizens' belief as the outbreak will damage the countries' functional capacity. Technical efficiency is used maximally to gain total control of the conditions. This study aims to measure the relative efficiency level of Southeast Asian countries in dealing with COVID-19 pandemic over one year. Methods: The relative efficiency level of the most successful countries in Southeast Asia in managing COVID-19 infection was determined using Frontier 4.1 through Stochastic Frontier Analysis (SFA) and Excel software. The technical efficiency of the SFA model is defined as the ratio of observed output to maximum feasible production. If the country's technical efficiency (TE) is greater than 80%, it is the most effective in Southeast Asia at managing COVID-19 infection, but if it is less than 80% or close to 0, it is inefficient. Results: This research aims at the COVID-19 epidemic in a Southeast Asian country, where the country with the highest technical efficiency score is the most efficient and indicates the country's ability to deal with the COVID-19 outbreak without any complications. Laos was ranked first (TE = 0.99901), with a technical efficiency score that was higher than that of most other Southeast Asian countries. Singapore comes in second position with a technical efficiency score of 0.99882. Brunei is in third place for COVID-19, with a technical efficiency score of 0.99870. Cambodia is in last place, with a score of 0.84675 for technical efficiency. Conclusion: Laos is the highest technical efficiency score among the southeast Asian countries. Various things that can lead to inefficiency include lack of awareness about standard operating procedures (SOP) among the causes of COVID-19 case infection in the workplace, and the community continues to increase. This condition may also be due to the lack of medication or vaccines to cure COVID-19. All communities around the world are expected to adopt standard operating procedures (SOP) such as wearing face masks, hand sanitizers, and social distance to curb the increasingly violent spread of COVID-19. © 2021 Tehran University of Medical Sciences.

A new hybrid conjugate gradient algorithm for optimization models and its application to regression analysis

The hybrid conjugate gradient (CG) method is among the efficient variants of CG method for solving optimization problems. This is due to their low memory requirements and nice convergence properties. In this paper, we present an efficient hybrid CG method for solving unconstrained optimization models and show that the method satisfies the sufficient descent condition. The global convergence prove of the proposed method would be established under inexact line search. Application of the proposed method to the famous statistical regression model describing the global outbreak of the novel COVID-19 is presented. The study parameterized the model using the weekly increase/decrease of recorded cases from December 30, 2019 to March 30, 2020. Preliminary numerical results on some unconstrained optimization problems show that the proposed method is efficient and promising. Furthermore, the proposed method produced a good regression equation for COVID-19 confirmed cases globally. © 2021 Institute of Advanced Engineering and Science. All rights reserved.