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  1. 1

    Long term energy demand forecasting based on hybrid, optimization: Comparative study by Musa, Wahab, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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    Article
  2. 2

    Harmony search-based robust optimal controller with prior defined structure by Rafieishahemabadi, Ali

    Published 2013
    “…In this approach, a combination of interacting two levels HS optimization algorithm is presented. In the first level, a new method for analytical formulation of integral square error cost function based on controller variables is elaborated for performance evaluation purposes by the proposed optimization algorithm. …”
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  3. 3

    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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  4. 4

    Improved smoothed functional algorithmsoptimized pid controller for efficient speed regulation of wind turbines by Mohd Ashraf, Ahmad, Yoganathan, G., Muhammad Ikram, Mohd Rashid, Hao, Mok Ren, Mohd Zaidi, Mohd Tumari

    Published 2025
    “…This study introduces a novel approach for PID controller tuning in wind turbine systems using single-agent optimization methods, specifically the memory smoothed functional algorithm (MSFA) and norm-limited smoothed functional algorithm (NL-SFA). …”
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  5. 5

    MOSDA: A proposal for multiple objective spiral dynamics algorithm by A. R.A., Azwan, Ahmad Nor Kasruddin, Nasir, Sha'akmal, S., A.R.M., Sawal

    Published 2018
    “…It has a good elitism strategy and has a simple structure. A method called “archive method” that is used in multi-objective particle swarm optimization (MOPSO) is adopted into SDA to develop its multiobjective (MO) type algorithm. …”
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  6. 6
  7. 7

    A hybrid model of system dynamics and genetic algorithm to increase crude palm oil production in Malaysia by Mohd Zabid, M. Faeid

    Published 2018
    “…In this research, a hybrid model of system dynamics (SD) and genetic algorithm (GA) was developed to determine the optimal policy in increasing the CPO production in Malaysia. …”
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  8. 8

    Controller placement problem in the optimization of 5G based SDN and NFV architecture by Ibrahim, Abeer Abdalla Zakaria

    Published 2021
    “…A heuristic called dynamic mapping and multi-stage CPP algorithm (DMMCPP) was developed to solve CPP as resource allocation in a distributed 5G-SDN-NFV-based network. …”
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  9. 9

    Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid by Abdul Hamid, Zulkiffli

    Published 2013
    “…At first, in producing a good optimization algorithm, a hybridization technique was proposed for adopting the finest features of two different algorithms; namely the Genetic Algorithm (GA) and continuous domain Ant Colony Optimization (ACOr). …”
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  10. 10

    Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid by Abdul Hamid, Zulkiffli

    Published 2013
    “…At first, in producing a good optimization algorithm, a hybridization technique was proposed for adopting the finest features of two different algorithms; namely the Genetic Algorithm (GA) and continuous domain Ant Colony Optimization (ACOr). …”
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  11. 11

    Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain by Sadrnia, Abdolhossein

    Published 2014
    “…The Multiobjective GSA (MOGSA) algorithm is adopted and then programmed using MATLAB software particularly to the MOACLSC. …”
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  12. 12

    Metaheuristic algorithms for solving lot-sizing and scheduling problems in single and multi-plant environments / Maryam Mohammadi by Mohammadi, Maryam

    Published 2015
    “…Metaheuristic approaches namely genetic algorithm, particle swarm optimization, artificial bee colony, simulated annealing, and imperialist competitive algorithm are adopted for the optimization procedures. …”
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  13. 13

    Development of optimized maintenance scheduling model for coal-fired power plant boiler by Noor Fazreen Binti Ahmad Fuzi, Ms.

    Published 2023
    “…Literature revealed that mathematical methods and metaheuristic algorithms are common approaches in solving combinatorial optimization problems with a large search space in a reasonable computational run time. …”
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  14. 14

    SVM, ANN, and PSF modelling approaches for prediction of iron dust minimum ignition temperature (MIT) based on the synergistic effect of dispersion pressure and concentration by Arshad, U., Taqvi, S.A.A., Buang, A., Awad, A.

    Published 2021
    “…The cubic kernel function was found suitable for training SVMs. Besides, a feed-forward artificial neural network with the backpropagation algorithm and a polynomial surface fit model have also been developed to predict the MIT. …”
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  15. 15

    Optimized fuzzy logic sliding mode control with proportional-integral-derivative for an electrohydraulic actuator system by Ghani, Muhamad Fadli

    Published 2023
    “…The proposed control strategy was designed with the switching function modification based on an FL approach in the conventional SMC algorithm called FLSMC. …”
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  16. 16

    Energy balancing mechanisms for decentralized routing protocols in wireless sensor networks by Saleh, Ahmed Mohammed Shamsan

    Published 2012
    “…It is based on Ant Colony Optimization (ACO) meta heuristic, which is adopted to enhance the paths with the best-quality function. …”
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  17. 17

    Enhancing reservoir simulation models with genetic algorithm optimized neural networks across diverse climatic zones / Saad Mawlood Saab by Saad Mawlood , Saab

    Published 2025
    “…The research improved the predictive models by integrating them with the Genetic Algorithm (GA). The optimizer algorithm (i.e., GA) determines the optimal input variables and internal parameters in the prediction models. …”
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  18. 18

    Long-term optimal planning for renewable based distributed generators and plug-in electric vehicles parking lots toward higher penetration of green energy technology by ALAhmad A.K., Verayiah R., Shareef H., Ramasamy A.

    Published 2025
    “…Moreover, to ensure realism, the model incorporates uncertainties related to stochastic variables such as the intermittent nature of RESs, EV energy and time variables, loads, and energy price fluctuations, using Monte Carlo Simulation (MCS) and the backward reduction method (BRM). A hybrid optimization algorithm addresses the proposed objectives, combining the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO) to minimize the three distinct objective functions concurrently. …”
    Article
  19. 19

    Modeling and Optimization of Tapered Rectangular Thin-walled Columns Subjected to Oblique Loading for Impact Energy Absorption by Siti Aishah, Rusdan, Tarlochan, Faris, Mohamad Rusydi, Mohamad Yasin

    Published 2013
    “…RS model using quadratic polynomial function is given as equation (1) below. The optimal design is obtained by using the constrained nonlinear multivariable optimization algorithm provided by MATLAB. …”
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  20. 20

    Model input and structure selection in multivariable dynamic modeling of batch distillation column pilot plant / Ilham Rustam by Rustam, Ilham

    Published 2015
    “…Further, after a careful investigation into the OLS algorithm, it was shown that the ERR technique which is an essential part of the algorithm to reach model parsimony, has led the resultant model to select an incorrect model terms albeit some improvement in model selection criteria and validation method adopted in this study. …”
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