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  1. 1
    Comparative study of modified BFGS and new scale modified BFGS for solving unconstrained optimization / Shahirah Atikah Mohamad Husnin

    Comparative study of modified BFGS and new scale modified BFGS for solving unconstrained optimization / Shahirah Atikah Mohamad Husnin by Mohamad Husnin, Shahirah Atikah

    Published 2018
    “…These methods were tested with several selected functions by using code Maple 18 software. …”
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  2. 2
    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern

    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

    Published 2012
    “…Two methods of optimization are used for CBLL. They are Cross Entropy and also Genetic Algorithm. …”
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  3. 3
    A memory-based gravitational search algorithm for enhancing minimum variance distortionless response beamforming

    A memory-based gravitational search algorithm for enhancing minimum variance distortionless response beamforming by Darzi S., Sieh Kiong T., Tariqul Islam M., Rezai Soleymanpour H., Kibria S.

    Published 2023
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  4. 4
    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems

    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems by Zulkifli, Munierah, Abd Rahmin, Nor Aliza, Wah, June Leong

    Published 2023
    “…Stochastic gradient descent (SGD) is one of the most common algorithms used in solving large unconstrained optimization problems. …”
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  5. 5
    Improved Fast Fuzzy C-Means Algorithm for Medical MR Images Segmentation

    Improved Fast Fuzzy C-Means Algorithm for Medical MR Images Segmentation by Li, Min, Huang, Tinglei, Zhu, Gangqiang

    Published 2008
    “…Using this method, an optimal classification rate is obtained in the test dataset, which includes large stochastic noises. …”
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  6. 6
    A modified n-th section line search in conjugate gradient methods for solving unconstrained optimization / Muhammad Imza Fakhri Jinudin

    A modified n-th section line search in conjugate gradient methods for solving unconstrained optimization / Muhammad Imza Fakhri Jinudin by Jinudin, Muhammad Imza Fakhri

    Published 2018
    “…All algorithms are written and executed using Maple 16 software. …”
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  7. 7
    Development of optimization Alghorithm for uncertain non-linear dynamical system

    Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

    Published 2004
    “…Based on the results of these simulations, we compared the number of iterations needed by each algorithm to arrive at the optimal solution and the CPU time taken for each algorithm to execute the search. …”
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    Monograph
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  8. 8
    Combined heat and power (CHP) economic dispatch solved using Lagrangian relaxation with surrogate subgradient multiplier updates

    Combined heat and power (CHP) economic dispatch solved using Lagrangian relaxation with surrogate subgradient multiplier updates by Sashirekha A., Pasupuleti J., Moin N.H., Tan C.S.

    Published 2023
    “…Flexibility for the choice of algorithm is given at the lower levels optimization techniques with the condition that the algorithm is able to improve its search at each iteration. …”
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  9. 9
    OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM

    OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM by WAHYUNGGORO, OYAS WAHYUNGGORO

    Published 2011
    “…Many tuning methods for PID controller have been developed, and one of them is based on natural evolution, the genetic algorithm (GA). …”
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  10. 10
    Artificial Immune System Based Remainder Method for Multimodal Mathematical Function Optimization

    Artificial Immune System Based Remainder Method for Multimodal Mathematical Function Optimization by Yap, David F. W., Koh, S. P., Tiong, S. K.

    Published 2011
    “…Conversely, Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) have been used efficiently in solving complex optimization problems, but they have an inclination to converge prematurely. …”
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  11. 11
    Memoryless modified symmetric rank-one method for large-scale unconstrained optimization

    Memoryless modified symmetric rank-one method for large-scale unconstrained optimization by Modarres, Farzin, Abu Hassan, Malik, Leong, Wah June

    Published 2009
    “…In this study, we present a scaled memoryless modified Symmetric Rank-One (SR1) algorithm and investigate the numerical performance of the proposed algorithm for solving large-scale unconstrained optimization problems. …”
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  12. 12
    Modified Sumudu Transform Analytical Approximate Methods For Solving Boundary Value Problems

    Modified Sumudu Transform Analytical Approximate Methods For Solving Boundary Value Problems by Al-Nemrat, Asem Mustafa Moh’ad

    Published 2019
    “…In this algorithm, the convolution theorem has been used to find an optimal Lagrange multiplier.…”
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  13. 13
    Modified Sumudu Transform Analytical Approximate Methods For Solving Boundary Value Problems

    Modified Sumudu Transform Analytical Approximate Methods For Solving Boundary Value Problems by Al-Nemrat, Asem Mustafa Moh’ad

    Published 2019
    “…In this algorithm, the convolution theorem has been used to find an optimal Lagrange multiplier.…”
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  14. 14
    Data Analysis using Particle Swarm Optimization Algorithm

    Data Analysis using Particle Swarm Optimization Algorithm by Tai, Zu Jie

    Published 2015
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    Final Year Project / Dissertation / Thesis
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  15. 15
    Comparative analysis of line search methods in the Steepest Descent algorithm for unconstrained optimization problems / Ahmad Zikri Shukeri, Puteri Qurratu Ain Megat Sulzamzamendi and Suhaida Ibrahim

    Comparative analysis of line search methods in the Steepest Descent algorithm for unconstrained optimization problems / Ahmad Zikri Shukeri, Puteri Qurratu Ain Megat Sulzamzamendi... by Shukeri, Ahmad Zikri, Megat Sulzamzamendi, Puteri Qurratu Ain, Ibrahim, Suhaida

    Published 2024
    “…The result from this study is choosing FMRI algorithm using exact line search to get faster convergence rate which means that the algorithm achieves a high level of accuracy in fewer iterations compared to using other algorithms and inexact line search.…”
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  16. 16
    Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization

    Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization by Yap, David F. W., Koh, S. P., Tiong, S. K.

    Published 2011
    “…Alternatively,Genetic Algorithms (GAs) and Particle Swarm Optimization(PSO) have been used efficiently in solving complex optimization problems, but they have a tendency to converge prematurely. …”
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  17. 17
    Mathematical function optimization using AIS antibody remainder method

    Mathematical function optimization using AIS antibody remainder method by Yap, David F. W., Koh, S. P., Tiong, S. K.

    Published 2011
    “…Alternatively, Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) have been used efficiently in solving complex optimization problems, but they have a tendency to converge prematurely. …”
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  18. 18
    Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak

    Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak by Emily Sing Kiang, Siew

    Published 2025
    “…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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  19. 19
    SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique

    SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique by Doroody C., Tiong S.K., Darzi S.

    Published 2023
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  20. 20
    Modified quasi-Newton type methods using gradient flow system for solving unconstrained optimization

    Modified quasi-Newton type methods using gradient flow system for solving unconstrained optimization by Yap, Chui Ying

    Published 2016
    “…We investigate the possible use of control theory, particularly theory on gradient ow system to derive some modified line search and trust region methods for optimization. …”
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