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  1. 1
    Optimizing the SEIRD model for COVID-19 in Malaysia using pymoo framework

    Optimizing the SEIRD model for COVID-19 in Malaysia using pymoo framework by Abdul Hadi, Muhammad Salihi, Amran, Muhammad Aiman Haziqh, Zulkarnain, Norsyahidah

    Published 2025
    “…However, the introduction of time-dependent coefficients in both models increases the number of optimization variables. To solve this, the Nelder-Mead and Pattern Search algorithms were recommended. …”
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  2. 2
    Fitting time-varying coefficients SEIRD model to Covid-19 cases in Malaysia

    Fitting time-varying coefficients SEIRD model to Covid-19 cases in Malaysia by Zulkarnain, Norsyahidah, Abdul Hadi, Muhammad Salihi, Mohammad, Nurul Farahain, Shogar, Ibrahim

    Published 2023
    “…Nelder-Mead outperforms the other optimization algorithm with the least error. …”
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  3. 3
    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models

    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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  4. 4
    Study of nature inspired computing (NIC) technique for optimal reactive power dispatch problems

    Study of nature inspired computing (NIC) technique for optimal reactive power dispatch problems by Sulaiman, Mohd Herwan

    Published 2017
    “…In this research, new nature-inspired meta-heuristic optimization algorithms namely moth-flame optimizer (MFO) and Ant Lion Optimizer (ALO) were implemented to address the optimal reactive power dispatch (ORPD) problems. …”
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    Research Report
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  5. 5
    Optimized clustering with modified K-means algorithm

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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    Thesis
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  6. 6
    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising

    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising by Al-Dabbagh, Mohanad Dawood, Al-Dabbagh, Rawaa Dawoud, Raja Abdullah, Raja Syamsul Azmir, Hashim, Fazirulhisyam

    Published 2015
    “…As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. …”
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  7. 7
    Mixed variable ant colony optimization technique for feature subset selection and model selection

    Mixed variable ant colony optimization technique for feature subset selection and model selection by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
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  8. 8
    Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River

    Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River by Katipo?lu O.M., Kartal V., Pande C.B.

    Published 2025
    “…This study combined models such as the artificial neural network (ANN) algorithm with the Firefly algorithm (FA) and Artificial Bee Colony (ABC) optimization techniques for the estimation of monthly SL values in the �oruh River in Northeastern Turkey. …”
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  9. 9
    Process Planning Optimization In Reconfigurable Manufacturing Systems

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…(i) what decision making models and (ii) what computational techniques, provide an optimal manufacturing process planning solution in a multidimensional decision variables space? …”
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  10. 10
    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm

    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2025
    “…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. …”
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  11. 11
    Enhanced Flipping Technique to Reduce Variability in Image Steganography

    Enhanced Flipping Technique to Reduce Variability in Image Steganography by Kamil S., Abdullah S.N.H.S., Hasan M.K., Bohani F.A.

    Published 2023
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  12. 12
    Global Particle Swarm Optimization for High Dimension Numerical Functions Analysis

    Global Particle Swarm Optimization for High Dimension Numerical Functions Analysis by Jamian, J.J., Abdullah, M.N., Mokhlis, Hazlie, Mustafa, M.W., Bakar, Ab Halim Abu

    Published 2014
    “…The Particle Swarm Optimization (PSO) Algorithm is a popular optimization method that is widely used in various applications, due to its simplicity and capability in obtaining optimal results. …”
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  13. 13
    An Application of Cuckoo Search Algorithm for Solving Optimal Chiller Loading Problem for Energy Conservation

    An Application of Cuckoo Search Algorithm for Solving Optimal Chiller Loading Problem for Energy Conservation by M. H., Sulaiman, Muhammad Ikram, Mohd Rashid, Mohd Rusllim, Mohamed, Omar, Aliman, Hamdan, Daniyal

    Published 2014
    “…This paper presents a recent swarm intelligence technique viz. Cuckoo Search Algorithm (CSA) for solving the Optimal Chiller Loading (OCL) problem for energy conservation. …”
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  14. 14
    A MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR WELLBORE TRAJECTORY DESIGN

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

    Published 2021
    “…To address this issue, a new hybridization of cellular automata (CA) technique with grey wolf optimization (GWO) and particle swarm optimization (PSO) algorithms is proposed in this work which solves these three optimization objectives of drilling through 17 tuning variables. …”
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  15. 15
    A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant

    A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant by Bunyamin M.A., Yap K.S., Aziz N.L.A.A., Tiong S.K., Wong S.Y., Kamal M.F.

    Published 2023
    “…The LR is one of the approaches that model the relationship between an output dependant variable, y, with one or more explanatory variables or inputs which denoted as x. …”
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  16. 16
    Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks

    Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks by Islam, B., Baharudin, Z., Nallagownden, P.

    Published 2015
    “…A hybrid approach that combines ANN and an evolutionary optimization technique, genetic algorithm (GA) is used for the development of a short term load forecast (STLF) model. …”
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  17. 17
    OPTIMIZATION OF DESIGN PARAMETERS FOR A VARIABLE FREQUENCY 3-PHASE INDUCTION MOTOR

    OPTIMIZATION OF DESIGN PARAMETERS FOR A VARIABLE FREQUENCY 3-PHASE INDUCTION MOTOR by APPLANAIDU, VISHNUV ARTHA

    Published 2009
    “…The objective function achieved from the design are cost, efficiency and weight. The optimization technique used to optimize this objective functions is Genetic Algorithm (GA) which is a Non -Linear Programming technique. …”
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  18. 18
    Loss Minimisation by Optimal Reactive Power Dispatch Using Cuckoo Search Algorithm

    Loss Minimisation by Optimal Reactive Power Dispatch Using Cuckoo Search Algorithm by M. H., Sulaiman, Muhammad Ikram, Mohd Rashid, Omar, Aliman, Mohd Rusllim, Mohamed, Abu Zaharin, Ahmad, Mohd. Shafie, Bakar

    Published 2014
    “…This paper presents a Swarm Intelligence (SI) technique namely Cuckoo Search Algorithm (CSA) which is inspired by parasitic behaviour of Cuckoo birds in reproduction strategy to obtain loss minimisation by solving the Optimal Reactive Power Dispatch (ORPD) problem. …”
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  19. 19
    Optimal Reactive Power Dispatch Solution by Loss Minimization Using Moth-Flame Optimization Technique

    Optimal Reactive Power Dispatch Solution by Loss Minimization Using Moth-Flame Optimization Technique by Rebecca Ng, Shin Mei, Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Hamdan, Daniyal

    Published 2017
    “…In this paper, a newly surfaced nature-inspired optimization technique called moth-flame optimization(MFO) algorithm is utilized to address the optimal reactive power dispatch (ORPD) problem. …”
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  20. 20
    Literature Review of Optimization Techniques for Chatter Suppression In Machining

    Literature Review of Optimization Techniques for Chatter Suppression In Machining by A. R., Yusoff, Mohamed Reza Zalani, Mohamed Suffian, Mohd Yusof, Taib

    Published 2011
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