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  1. 1
    Efficient genetic partitioning-around-medoid algorithm for clustering

    Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

    Published 2019
    “…In general, genetic based clustering algorithms showed the ability to reach near global optimal solution. …”
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  2. 2
    Optimal demand response of solar energy generation using Genetic Algorithm / Muhammad Asyraaf Adlan

    Optimal demand response of solar energy generation using Genetic Algorithm / Muhammad Asyraaf Adlan by Adlan, Muhammad Asyraaf

    Published 2025
    “…The method involves collecting data from the solar energy project of UiTM Kampus Dungun, implementing GA for optimization, and evaluating its performance based on the fitness value and convergence trends. …”
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  3. 3
    Online Programming Judge System (UOJ)

    Online Programming Judge System (UOJ) by Tran , Quang Trung

    Published 2013
    “…The system has the function to judge programming code by evaluating the output that the program produced. …”
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  4. 4
    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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  5. 5
    An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications.

    An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications. by S. Ahmed, Bestoun, Enoiu, Eduard, Afzal, Wasif, Kamal Z., Zamli

    Published 2020
    “…The results show the Q-EMCQ is also capable of outperforming the original EMCQ as well as several recent meta/hyper-heuristic including modified choice function, Tabu high-level hyperheuristic, teaching learning-based optimization, sine cosine algorithm, and symbiotic optimization search in clustering quality within comparable execution time.…”
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  6. 6
    Optimization Of Fuzzy Logic Controllers With Genetic Algorithm For Two-Part-Type And Re-Entrant Production Systems

    Optimization Of Fuzzy Logic Controllers With Genetic Algorithm For Two-Part-Type And Re-Entrant Production Systems by Homayouni, Seyed Mahdi

    Published 2008
    “…Furthermore, genetic algorithm (GA) has been used to optimize the FLCs performance. …”
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  7. 7
    Using genetic algorithms to optimise land use suitability

    Using genetic algorithms to optimise land use suitability by Pormanafi, Saeid

    Published 2012
    “…In this study, under environmentfriendliness objective, based on multi-agent genetic algorithms, was developed a geospatial model for the land use allocation. …”
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  8. 8
    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh

    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

    Published 2015
    “…DE has effectively solved various global optimization problems, including benchmark functions. …”
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  9. 9
    Computational intelligence based power system security assessment and improvement under multi-contingencies conditions / Nor Rul Hasma Abdullah

    Computational intelligence based power system security assessment and improvement under multi-contingencies conditions / Nor Rul Hasma Abdullah by Abdullah, Nor Rul Hasma

    Published 2012
    “…The minimizations of SVSI and transmission loss are used as two separate objective functions for the development of optimization technique. …”
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  10. 10
    Study on the microbial growth inhibition by using pineapple leaves juice

    Study on the microbial growth inhibition by using pineapple leaves juice by Amirah, Ya'acob

    Published 2022
    “…The minimizations of SVSJ and transmission loss are used as two separate objective functions for the development of optimization technique. …”
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  11. 11
    Computational intelligence based power system security assessment and improvement under multicontigencies conditions

    Computational intelligence based power system security assessment and improvement under multicontigencies conditions by Nor Rul Hasma, Abdullah

    Published 2012
    “…The minimizations of SVSJ and transmission loss are used as two separate objective functions for the development of optimization technique.The effect of reactive power load variation.on transmission loss in the system is also investigated.Consequently,the EP optimization technique is extended for the evaluation of the operating generator scheduling (OGS) to be applied on reactive power control in power system.The results obtained from the study can be used by the power system operators to make a decision either to achieve minimal SVSJ, minimal transmission loss or minimal installation cost.This has also avoided all generators to dispatch power at the same time.Finally,a novel multi-objective Constrained Reactive Power Control (CRPC) algorithm using the state-of-the-art of EP for voltage stability improvement has been developed.A performance comparison with Artificial Immune System (AIS) in terms of SVSJ and loss minimization was made and it is found that the proposed algorithm has been able to produce better results as compared to AIS.The contributions of the studies among the others are the development EP and AIS engine for CPP considered multi-contingencies (N-ni),the development of EP and AIS engine for FACTS installation considered multi-contingencies(N-m) for the determination of FACTS placement using SVSI and optimal sizing of FACTS using EP and AIS, the development of new technique for OGS based on EP optimization technique and the development of multi-objective EP and AIS engines for CRPC considered multi-contingencies (N-m).…”
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  12. 12
    A Compromise Programming to Task Assignment Problem in Software Development Project

    A Compromise Programming to Task Assignment Problem in Software Development Project by Son, N.T., Jaafar, J., Aziz, I.A., Anh, B.N., Binh, H.D., Aftab, M.U.

    Published 2021
    “…This study aims to propose an approach based on multi-objective combinatorial optimization to do this automatically. …”
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  13. 13
    Development of an integrated scheduling model for handling equipment in automated port container terminals

    Development of an integrated scheduling model for handling equipment in automated port container terminals by Sadeghian, Syed Hamidreza

    Published 2014
    “…In addition, results proved that the modified meta-heuristic algorithm is able to find near optimal solutions and on average, the solutions found by the GA algorithm are only 0.2% worse than the optimal solutions and in the worst case in the test cases this difference is 2.3% which is acceptable. …”
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  14. 14
    Hybrid evolutionarybarnacles mating optimisation-artificial neural network based technique for solving economic power dispatch planning and operation / Nor Laili Ismail

    Hybrid evolutionarybarnacles mating optimisation-artificial neural network based technique for solving economic power dispatch planning and operation / Nor Laili Ismail by Ismail, Nor Laili

    Published 2024
    “…The third algorithm was validated on IEEE 30-Bus RTS only. Comparative studies were conducted concerning the traditional Evolutionary Programming (EP) and Barnacles Mating Optimiser (BMO) for performance evaluation of HEBMO and MOHEBMO. …”
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  15. 15
    New optimization feature for the developed open cnc controller based on ISO 6983 and ISO 14649

    New optimization feature for the developed open cnc controller based on ISO 6983 and ISO 14649 by Obayes, Noor Hatem

    Published 2021
    “…A new optimized system was developed based on open architecture control (OAC) technology and interpreted STEP-NC (Standard for the Exchange of Product Model Data) programming approaches. …”
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  16. 16
    Optimal forwarding routing protocol in ipv6-based wireless sensor network

    Optimal forwarding routing protocol in ipv6-based wireless sensor network by Jamil, Ansar

    Published 2009
    “…Then, developed code is programmed into TelosB radio sensors boards in WSN test beds. …”
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  17. 17
    Power System State Estimation In Large-Scale Networks

    Power System State Estimation In Large-Scale Networks by NURSYARIZAL MOHD NOR, NURSYARIZAL

    Published 2010
    “…The gain and the Jacobian matrices associated with the basic algorithm require large storage and have to be evaluated at every iteration, resulting in more computation time. …”
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  18. 18
    Multiple and solid data background scheme for testing static single cell faults on SRAM memories

    Multiple and solid data background scheme for testing static single cell faults on SRAM memories by Zakaria, Nor Azura

    Published 2013
    “…Therefore, the purpose of this thesis is to introduce a Data Background (DB) scheme to generate an optimal March Test Algorithm (MTA) for detecting faults of memory that are undetectable using existing algorithms. …”
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  19. 19
    Neural network methods to solve the Lane–Emden type equations arising in thermodynamic studies of the spherical gas cloud model

    Neural network methods to solve the Lane–Emden type equations arising in thermodynamic studies of the spherical gas cloud model by Ahmad, Iftikhar, Zahoor Raja, Muhammad Asif, Bilal, Muhammad, Ashraf, Farooq

    Published 2017
    “…ANNs are used in an unsupervised manner to construct the energy function of the system model. Strength of efficient local optimization procedures based on active-set (AS), interior-point (IP) and sequential quadratic programming (SQP) algorithms is used to optimize the energy functions. …”
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  20. 20
    Development of wwm system using mlnn-ga for ph prediction of water quality in catchment area

    Development of wwm system using mlnn-ga for ph prediction of water quality in catchment area by Muhammad Aznil, Ab Aziz

    Published 2021
    “…MLNN-GA contain three hidden layers and Genetic Algorithm (GA) will optimize the weight of neural network during the training process. …”
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