Search Results - (( using function method algorithm ) OR ( _ optimization modified algorithm ))

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  1. 1

    A modified discrete filled function algorithm for solving nonlinear discrete optimization problems by Woon, Siew Fang, Rehbock, Volker, Loxton, Ryan

    Published 2012
    “…The discrete filled function method is a global optimization tool for searching for best solution amongst multiple local optima.This method has proven useful for solving large-scale discrete optimization problems.In this paper, we consider a standard discrete filled function algorithm in the literature and then propose a modification to increase its efficiency.…”
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  2. 2

    Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane by Julakha, Jahan Jui, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

    Published 2021
    “…In the HMVOSCA algorithm, the new position updating mechanism of the traditional MVO method is modified based on the sine function and cosine function which is taken from the Sine Cosine Algorithm (SCA). …”
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  3. 3

    An experimental study of modified black hole algorithms by Mohammed, Suad Khairi

    Published 2018
    “…The algorithms are evaluated based on unimodal, multimodal, hybrid, and composite functions in CEC2014 benchmark test functions. …”
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    Thesis
  4. 4

    A MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR WELLBORE TRAJECTORY DESIGN by BISWAS, KALLOL

    Published 2021
    “…True measured depth (TMD), torque, and strain energy are used as objective functions to evaluate the wellbore trajectory design in this work. …”
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  5. 5

    Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

    Published 2018
    “…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
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  6. 6

    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

    Published 2024
    “…However, the complexity significantly rises when dealing with multi objective functions. The Modified Adaptive Bats Sonar Algorithm (MABSA), initially designed for single objective optimization and inspired by colony bats' echolocation, has demonstrated efficiency with its simple structure and reduced computation time. …”
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  7. 7

    Optimal power flow using the Jaya algorithm by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

    Published 2016
    “…Unlike other population-based optimization methods, no algorithm-particular controlling parameters are required for this algorithm. …”
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    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

    Published 2021
    “…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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  11. 11

    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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  12. 12

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, Hishamuddin, Abd. Samad, M. F., Ahmad, Robiah, Yaacob, M. S.

    Published 2007
    “…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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  13. 13

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, H., Samad, M. F. A., Ahmad, R., Yaacob, M. S.

    Published 2007
    “…he genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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  14. 14

    An Improved Artificial Immune System Based On Antibody Reminder Method For Mathematical Function Optimization by Yap, David F. W., Habibullah, Akbar, Koh, S. P., Tiong, S. K.

    Published 2010
    “…Artificial immune system (AIS) is one of the nature inspired algorithm for optimization problem. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability. …”
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  15. 15

    New Quasi-Newton Equation And Method Via Higher Order Tensor Models by Gholilou, Fahimeh Biglari

    Published 2010
    “…By using a new equation, the BFGS method is modified. …”
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  16. 16

    An improved artificial immune system based on antibody remainder method for mathematical function optimization by Yap D.F.W., Habibullah A., Koh S.P., Tiong S.K.

    Published 2023
    “…Artificial immune system (AIS) is one of the nature-inspired algorithm for optimization problem. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability. …”
    Conference paper
  17. 17

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

    Published 2011
    “…Artificial immune system (AIS) is one of the natureinspired algorithm for solving optimization problem. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability. …”
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  18. 18

    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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    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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