Search Results - "Kaelo, P."

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  1. 1

    A globally convergent projection method for a system of nonlinear monotone equations by Kaelo, P., Koorapetse, M.

    “…In this paper, a new conjugate gradient-based projection method for solving a system of nonlinear monotone equations is proposed. The method can be viewed as…”
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  2. 2

    A numerical study of some modified differential evolution algorithms by Kaelo, P., Ali, M.M.

    Published in European journal of operational research (16-03-2006)
    “…Modifications in mutation and localization in acceptance rule are suggested to the differential evolution algorithm for global optimization. Numerical…”
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  3. 3

    Improved particle swarm algorithms for global optimization by Ali, M.M., Kaelo, P.

    Published in Applied mathematics and computation (01-03-2008)
    “…Particle swarm optimization algorithm has recently gained much attention in the global optimization research community. As a result, a few variants of the…”
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  4. 4

    Another Three-Term Conjugate Gradient Method Close to the Memoryless BFGS for Large-Scale Unconstrained Optimization Problems by Diphofu, T., Kaelo, P.

    Published in Mediterranean journal of mathematics (01-10-2021)
    “…In this paper, we propose a new three term conjugate gradient method, in which the search direction is close to the direction in the memoryless BFGS method…”
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  5. 5

    A Descent Generalized RMIL Spectral Gradient Algorithm for Optimization Problems by Sulaiman, Ibrahim M., Kaelo, P., Khalid, Ruzelan, Nawawi, Mohd Kamal M.

    “…This study develops a new conjugate gradient (CG) search direction that incorporates a well defined spectral parameter while the step size is required to…”
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  6. 6

    Globally convergent three-term conjugate gradient projection methods for solving nonlinear monotone equations by Koorapetse, Mompati S., Kaelo, P.

    Published in Arabian journal of mathematics (01-12-2018)
    “…In this paper, we propose two derivative-free conjugate gradient projection methods for systems of large-scale nonlinear monotone equations. The proposed…”
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  7. 7

    Self adaptive spectral conjugate gradient method for solving nonlinear monotone equations by Koorapetse, M., Kaelo, P.

    “…In this paper, we propose a self adaptive spectral conjugate gradient-based projection method for systems of nonlinear monotone equations. Based on its modest…”
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  8. 8

    A convergent hybrid three-term conjugate gradient method with sufficient descent property for unconstrained optimization by Diphofu, T., Kaelo, P., Tufa, A.R.

    Published in Topological algebra and its applications (21-06-2022)
    “…Conjugate gradient methods are very popular for solving large scale unconstrained optimization problems because of their simplicity to implement and low memory…”
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  9. 9

    A Globally Convergent Derivative-Free Projection Method for Nonlinear Monotone Equations with Applications by Kaelo, P., Koorapetse, M., Sam, C. R.

    “…In this paper, based on the theoretical effectiveness of quasi-Newton methods and the projection strategy, we propose a three-term derivative-free projection…”
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  10. 10

    An optimal choice Dai-Liao conjugate gradient algorithm for unconstrained optimization and portfolio selection by Sabi'u, Jamilu, Sulaiman, Ibrahim Mohammed, Kaelo, P., Malik, Maulana, Kamaruddin, Saadi Ahmad

    Published in AIMS mathematics (2024)
    “…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…”
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  11. 11

    A Scaled Derivative-Free Projection Method for Solving Nonlinear Monotone Equations by Koorapetse, M., Kaelo, P., Offen, E. R.

    “…Derivative-free projection methods are very effective and highly useful methods for solving large-scale nonlinear monotone equations. A lot of research is…”
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  12. 12

    Differential evolution algorithms using hybrid mutation by Kaelo, P, Ali, M M

    “…Differential evolution (DE) has gained a lot of attention from the global optimization research community. It has proved to be a very robust algorithm for…”
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  13. 13

    Some variants of the controlled random search algorithm for global optimization by KAELO, P, ALI, M. M

    “…We suggested some modications to the controlled random search (CRS) algorithm for global optimization. We introduce new trial point generation schemes in CRS,…”
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  14. 14

    Integrated crossover rules in real coded genetic algorithms by Kaelo, P., Ali, M.M.

    “…Modifications in crossover rules and localization of searches are suggested to the real coded genetic algorithms for continuous global optimization. Central to…”
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  15. 15

    An efficient modified PRP-FR hybrid conjugate gradient method for solving unconstrained optimization problems by Mtagulwa, Peter, Kaelo, P.

    Published in Applied numerical mathematics (01-11-2019)
    “…In this paper, a new hybrid conjugate gradient method for solving unconstrained optimization problems is proposed. The proposed method inherits the features of…”
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  16. 16

    A convergent modified HS-DY hybrid conjugate gradient method for unconstrained optimization problems by Mtagulwa, Peter, Kaelo, P.

    “…Conjugate gradient algorithm (method) is a very simple and powerful technique for solving large scale unconstrained optimization problems. In this paper a new…”
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  17. 17

    A derivative-free RMIL conjugate gradient projection method for convex constrained nonlinear monotone equations with applications in compressive sensing by Koorapetse, M., Kaelo, P., Lekoko, S., Diphofu, T.

    Published in Applied numerical mathematics (01-07-2021)
    “…In this paper, a derivative-free RMIL conjugate gradient projection method for solving large-scale nonlinear monotone equations with convex constraints is…”
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  18. 18

    An efficient hybrid conjugate gradient-based projection method for convex constrained nonlinear monotone equations by Koorapetse, Mompati, Kaelo, P.

    Published in Journal of interdisciplinary mathematics (18-08-2019)
    “…Conjugate gradient projection methods are widely used for solving large-scale nonlinear systems of monotone equations because of their low memory requirements…”
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  19. 19

    Probabilistic adaptations of point generation schemes in some global optimization algorithms by Kaelo, P., Ali, M. M.

    Published in Optimization methods & software (01-06-2006)
    “…Modifications in the trial point generation scheme are suggested to the differential evolution (de) and the controlled random search (crs) algorithm to improve…”
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