Maulana Malik
University of Indonesia
AlgorithmMathematical optimizationVirologyEconomicsReinsuranceMortality rateHamilton–Jacobi–Bellman equationBasic reproduction numberDescent (mathematics)Applied mathematicsPopulationFractional powerWolfe line searchUnconstrained optimizationLife insuranceMathematicsCentral processing unitFunction (mathematics)Convergence (routing)MedicineConjugate gradient methodSelection (genetic algorithm)Line searchBiology
30Publications
4H-index
19Citations
Publications 33
Newest
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 m...
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#1Auwal Bala Abubakar (Sefako Makgatho Health Sciences University)H-Index: 13
#2Poom Kumam (China Medical University (Taiwan))H-Index: 48
Last. Abdulkarim Hassan Ibrahim (King Mongkut's University of Technology Thonburi)H-Index: 12
view all 4 authors...
Abstract null null In this article, we propose a hybrid conjugate gradient (CG) scheme for solving unconstrained optimization problem. The search direction is a combination of the Polak–Ribiere–Polyak (PRP) and the Liu-Storey (LS) CG parameters and is close to the direction of the memoryless Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton scheme. Without the use of the line search, the search direction satisfies the descent condition and possesses the trust region property. The global conve...
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#1Basim A. HassanH-Index: 4
#2Maulana MalikH-Index: 4
view all 3 authors...
The quasi-Newton (QN) method are among the efficient variants of conjugate gradient (CG) method for solving unconstrained optimization problems. The QN method utilizes the gradients of the function while ignoring the available value information at every iteration. In this paper, we extended the Dai-Yuan [39] coefficient in designing a new CG method for large-scale unconstrained optimization problems. An interesting feature of our method is that its algorithm not only uses the available gradient ...
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#1S. Devila (UI: University of Indonesia)H-Index: 1
#2Maulana Malik (UI: University of Indonesia)H-Index: 4
Last. Wed Giyarti (Sunan Kalijaga Islamic University)
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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 t...
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#2Mustafa MamatH-Index: 16
Last. SukonoH-Index: 7
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#1Maulana Malik (UI: University of Indonesia)H-Index: 4
#2Auwal Bala Abubakar (Sefako Makgatho Health Sciences University)H-Index: 13
Last. Sukono (UNPAD: Padjadjaran University)H-Index: 7
view all 6 authors...
#2Mustafa MamatH-Index: 16
Last. Maulana MalikH-Index: 4
view all 5 authors...
Conjugate Gradient (CG) method is the most prominent iterative mathematical technique that can be useful for the optimization of both linear and non-linear systems due to its simplicity, low memory requirement, computational cost, and global convergence properties. However, some of the classical CG methods have some drawbacks which include weak global convergence, poor numerical performance both in terms of number of iterations and the CPU time. To overcome these drawbacks, researchers proposed ...
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#2Mustafa MamatH-Index: 16
Last. Maulana MalikH-Index: 4
view all 5 authors...
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#2Poom Kumam (King Mongkut's University of Technology Thonburi)H-Index: 48
#3Maulana MalikH-Index: 4
Last. Abdulkarim Hassan IbrahimH-Index: 12
view all 5 authors...
In this paper, we present a new hybrid conjugate gradient (CG) approach for solving unconstrained optimization problem. The search direction is a hybrid form of the Fletcher-Reeves (FR) and the Dai-Yuan (DY) CG parameters and is close to the direction of the memoryless Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton approach. Independent of the line search, the search direction of the new approach satisfies the descent condition and possess the trust region. We establish the global converge...
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