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  1. 1
    Broadening selection competitive constraint handling algorithm for faster convergence

    Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

    Published 2020
    “…The proposed algorithm has been evaluated using 24 benchmark functions. …”
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  2. 2
    Differential evolution for neural networks learning enhancement

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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  3. 3
    VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.

    VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS. by FAROOQ, HUMERA

    Published 2012
    “…A tool termed as VIGA-20 (Visualization of Genetic Algorithm using 2-0 Graph) is implemented to accomplish this goal. …”
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  4. 4
    Optimization of an extended H-infinity controller for unmanned helicopter control using multiobjective differential evolution (MODE)

    Optimization of an extended H-infinity controller for unmanned helicopter control using multiobjective differential evolution (MODE) by Tijani, Ismaila Bayo, Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus

    Published 2015
    “…Then apply the MODE-based algorithm to optimize the weighting function of the control problem formulation for optimal performance. …”
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  5. 5
    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
    “…The aim of the algorithm is to improve a controller performance (minimize the overshoot, settling time, IAE/ITAE and achieving zero steady state error) when used for a DC servomotor application. …”
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  6. 6
    A hyper-heuristic based strategy for image segmentation using multilevel thresholding

    A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

    Published 2025
    “…Apart from the best low-level heuristic, EMCQ also gives a chance to low-performing heuristics to search for the optimal threshold values using their probability density function. …”
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  7. 7
    A hyper-heuristic based strategy for image segmentation using multilevel thresholding

    A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

    Published 2025
    “…Apart from the best low-level heuristic, EMCQ also gives a chance to low-performing heuristics to search for the optimal threshold values using their probability density function. …”
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  8. 8
    Nonlinear modeling and control of a spark ignition engine idle speed / Hazem Mohamed

    Nonlinear modeling and control of a spark ignition engine idle speed / Hazem Mohamed by Hazem, Mohamed

    Published 1998
    “…The input output data was collected from an experimental four cylinder spark ignition engine, then this data is fitted to a NARMAX model using a radial basis function network trained by the orthogonal least squares algorithm. …”
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  9. 9
    Gradient-based mutation manta ray foraging optimization (gbm-mrfo) for solving constrained real-world problems

    Gradient-based mutation manta ray foraging optimization (gbm-mrfo) for solving constrained real-world problems by Ahmad Azwan, Abdul Razak, Ahmad Nor Kasruddin, Nasir

    Published 2022
    “…GbM-MRFO turn out to be a competitive optimization algorithm on solving constrained optimization problem of Three-bar Truss problem. …”
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  10. 10
    Evolving controllers for simulated car racing using differential evolution

    Evolving controllers for simulated car racing using differential evolution by Shi, Jun Long, Chin, Kim On, Teo, Jason Tze Wi, Tan, Tse Guan, Rayner Alfred, Patricia Anthony

    Published 2013
    “…This research result shows that DE performed well in TORCS even though a very simple fitness function was used. This indicates that DE has well-tuned the neural network weights to generate optimal and sub-optimal controllers in TORCS.…”
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  11. 11
    Novel farmland fertility algorithm based PIDPSS design for SMIB angular stability enhancement

    Novel farmland fertility algorithm based PIDPSS design for SMIB angular stability enhancement by Sabo, Aliyu, Abdul Wahab, Noor Izzri, Othman, Mohammad Lutfi, Mohd Jaffar, Mai Zurwatul Ahlam

    Published 2020
    “…For this study, design of proportional integral derivative (PID) PSS (PIDPSS) is proposed for damping oscillations and improve angular stability in single machine infinite bus (SMIB) power system modeled and simulated in MATLAB/SIMULINK. A new metaheuristics method called Farmland Fertility Algorithm (FFA) inspired by nature is proposed for optimal design of PIDPSS using a robust ISTSE objective function which had to be minimized. …”
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  12. 12
    Artificial Neural Controller Synthesis in Autonomous Mobile Cognition

    Artificial Neural Controller Synthesis in Autonomous Mobile Cognition by Kim On Chin, Jason Teo

    Published 2009
    “…This paper describes a new approach in using multi-objective evolutionary algorithms in evolving the neural network that acts as a controller for the phototaxis and radio frequency localization behaviors of a virtual Khepera robot simulated in a 3D, physics-based environment. …”
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  13. 13
    Artificial Neural Controller Synthesis in Autonomous Mobile Cognition

    Artificial Neural Controller Synthesis in Autonomous Mobile Cognition by Chin Kim On, Jason Teo

    Published 2009
    “…This paper describes a new approach in using multi-objective evolutionary algorithms in evolving the neural network that acts as a controller for the phototaxis and radio frequency localization behaviors of a virtual Khepera robot simulated in a 3D, physics-based environment. …”
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  14. 14
    Automatic generation of Swarm Robotic behaviors using multi-objective evolution

    Automatic generation of Swarm Robotic behaviors using multi-objective evolution by Chin, Kim On, Teo, Jason, Azali, Saudi

    Published 2009
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  15. 15
    Hybridization Of Deterministic And Metaheuristic Approaches In Global Optimization

    Hybridization Of Deterministic And Metaheuristic Approaches In Global Optimization by Goh, Khang Wen

    Published 2019
    “…The successful of Simplexed ABC method leads this research to develop a mechanism to transform those well-developed gradient based local deterministic optimization approaches into solving global optimization approaches. …”
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  16. 16
    Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons

    Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons by Yaseen, Zaher Mundher, Fu, Minglei, Wang, Chen, Mohtar, Wan Hanna Melini Wan, Deo, Ravinesh C., El-Shafie, Ahmed

    Published 2018
    “…The rolling mechanism method is applied to smooth out the dataset based on the antecedent values of the model inputs before being applied to the GM algorithm. The optimization of the input datasets selection was performed using auto-correlation (ACF) and partial auto-correlation (PACF) functions. …”
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  17. 17
    Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution

    Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution by Tijani, Ismaila B., Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus

    Published 2014
    “…This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data.The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. …”
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  18. 18
    A New Hybrid Approach Based On Discrete Differential Evolution Algorithm To Enhancement Solutions Of Quadratic Assignment Problem

    A New Hybrid Approach Based On Discrete Differential Evolution Algorithm To Enhancement Solutions Of Quadratic Assignment Problem by Asaad Shakir, Hameed, Mohd Aboobaider, Burhanuddin, Mutar, Modhi Lafta, Ngo, Hea Choon

    Published 2020
    “…The primary aim of this study is to propose a hybrid approach which combines Discrete Differential Evolution (DDE) algorithm and Tabu Search (TS) algorithm to enhance solutions of QAP model, to reduce the distances between the locations by finding the best distribution of N facilities to N locations, and to implement hybrid approach based on discrete differential evolution (HDDETS) on many instances of QAP from the benchmark. …”
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  19. 19
    Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution

    Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution by Ganesan, T., Elamvazuthi, I., Shaari, K.Z.K., Vasant, P.

    Published 2014
    “…In this chapter, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms: Differential Evolution (DE), Hopfield-Enhanced Differential Evolution (HEDE), and Gravitational Search Algorithm (GSA). …”
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  20. 20
    Resource allocation in coordinated multipoint long term evolution-advanced networks

    Resource allocation in coordinated multipoint long term evolution-advanced networks by Katiran, Norshidah

    Published 2015
    “…The resource allocation algorithm is developed through three phases, namely Low-Complexity Resource Allocation (LRA), Optimized Resource Allocation (ORA) and Cross-Layer Design of ORA (CLD-ORA). …”
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