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  1. 1
    Optimal placement of unified power flow controller by dynamic implementation of system-variable-based voltage-stability indices to enhance voltage stability

    Optimal placement of unified power flow controller by dynamic implementation of system-variable-based voltage-stability indices to enhance voltage stability by Ahmad, S., Albatsh, F.M., Mekhilef, Saad, Mokhlis, Hazlie

    Published 2016
    “…Furthermore, to verify the suitability of the explored locations, a comparative study has been conducted after placing UPFC in the present locations and other locations obtained using optimization techniques like particle swarm optimization (PSO), differential evolution (DE), genetic algorithm (GA), and bacteria foraging algorithm (BFA). …”
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  2. 2
    Optimizing dam and reservoir operations using machine learning

    Optimizing dam and reservoir operations using machine learning by Mohammad Abdullah Adib Almubaidin

    Published 2025
    text::Thesis
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  3. 3
    Dynamic probability selection for flower pollination algorithm based on metropolis-hastings criteria

    Dynamic probability selection for flower pollination algorithm based on metropolis-hastings criteria by Zamli, Kamal Zuhairi, Din, Fakhrud, Nasser, Abdullah, Ramli, Nazirah, Mohamed, Noraini

    Published 2021
    “…This paper proposed flower pollination algorithm metropolis-hastings (FPA-MH) based on the adoption of Metropolis-Hastings criteria adopted from the Simulated Annealing (SA) algorithm to enable dynamic selection of the pa probability. …”
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  4. 4
    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)

    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224) by Mahat, Nor Idayu, Engku Abu Bakar, Engku Muhammad Nazri, Zakaria, Ammar, Mohd Nazir, Mohd Amril Nurman, Misiran, Masnita

    “…This study developed an algorithm for statistical classification that enable ones to classify a future data to one of predetermined groups based on the measured data which facing two major threats; (i) multicollinearity among the measured variables and (ii) imbalanced groups. …”
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  5. 5
    Profit Optimization of a Refrigerated Gas Plant

    Profit Optimization of a Refrigerated Gas Plant by Yusoff, Nooryusmiza, Ramasamy , Marappagounder, Yusup, Suzana

    Published 2007
    “…This requires continuous re-evaluation of the operating conditions through an efficient optimization algorithm. …”
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  6. 6
    Profit Optimization of a Refrigerated Gas Plant

    Profit Optimization of a Refrigerated Gas Plant by Yusoff, Nooryusmiza, Ramasamy , Marappagounder, Yusup, Suzana

    Published 2007
    “…This requires continuous re-evaluation of the operating conditions through an efficient optimization algorithm. …”
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  7. 7
    Profit Optimization of a Refrigerated Gas Plant

    Profit Optimization of a Refrigerated Gas Plant by Yusoff, Nooryusmiza, Ramasamy , Marappagounder, Yusup, Suzana

    Published 2007
    “…This requires continuous re-evaluation of the operating conditions through an efficient optimization algorithm. …”
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  8. 8
    Information Theoretic-based Feature Selection for Machine Learning

    Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

    Published 2018
    “…The second test evaluates IFS in a controlled study using simulated datasets. …”
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  9. 9
    Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems

    Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems by Bashar AbedAl Mohdi Talal AlDeeb

    Published 2024
    “…The IWD is a recent metaheuristic population-based algorithm belonging to the swarm intelligent category which simulates the dynamic of the river systems. …”
    thesis::doctoral thesis
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  10. 10
    Capacity Planning For Mixed-Load Tester Under Demand And Testing Time Uncertainty

    Capacity Planning For Mixed-Load Tester Under Demand And Testing Time Uncertainty by Asih, Hayati Mukti

    Published 2018
    “…Currently,the company’s issue is low tester utilization of about 71%,well below the target of 96%.The objective of this research is to improve tester utilization while achieving the production target under uncertain demand and testing time and also to determine the break-even point on the testers required.A novel approach of integrating a mathematical model,robust optimization model,genetic algorithm,simulation model and cost–volume –profit analysis was developed.Firstly,a mathematical model of mixed-load tester was formulated.Next,a set of discrete scenarios was proposed to address uncertain demand and testing time.A robust optimization and genetic algorithm model was developed to optimize the number of testers under the described uncertainties.Next,these scenarios were simulated using the Pro Model simulation software to validate the proposed models and to evaluate throughput and tester utilization.Finally,the cost–volume–profit analysis was performed for scenarios that require additional testers at various levels of uncertainties.The results showed that the proposed solution improved tester utilization by 25% compared to the current system.This research has contribution by developing novel hybrid methodology and able to provide useful insights to assist company’s managers to plan and allocate resources according to variations in customers’ demands and testing time.…”
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  11. 11
    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio

    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio by Wang, B., Li, Y., Wang, S., Watada, J.

    Published 2018
    “…Then the proposed model is solved by a fuzzy simulation-based multi-objective particle swarm optimization algorithm, where the global best of each iteration is determined by an improved dominance times-based method. …”
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  12. 12
    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio

    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio by Wang, B., Li, Y., Wang, S., Watada, J.

    Published 2018
    “…Then the proposed model is solved by a fuzzy simulation-based multi-objective particle swarm optimization algorithm, where the global best of each iteration is determined by an improved dominance times-based method. …”
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  13. 13
    Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid

    Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid by Gaeid, Khalaf Salloum

    Published 2012
    “…This thesis aims at exploring the fault tolerant control of the IMs. This involves sensor based closed loop vector control for a healthy IM, Variable frequency with constant flux(V/F) closed loop for both stator open winding and stator short winding faults , V/F open loop to control the drive in case of minimum voltage fault and using the sensorless vector control in case of encoder faults. …”
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  14. 14
    Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems

    Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems by Tan, Joe Yee

    Published 2022
    “…In this case, the effectiveness and reliability of RMS is increase by combining the simulation with the optimization algorithm.…”
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  15. 15
    Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm

    Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm by Zuwairie, Ibrahim, Nor Hidayati, Abd Aziz, Nor Azlina, Ab. Aziz, Saifudin, Razali, Mohd Saberi, Mohamad

    Published 2016
    “…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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  16. 16
    Simulated Kalman Filter algorithms for solving optimization problems

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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  17. 17
    Angle Modulated Simulated Kalman Filter Algorithm for Combinatorial Optimization Problems

    Angle Modulated Simulated Kalman Filter Algorithm for Combinatorial Optimization Problems by Zulkifli, Md. Yusof, Zuwairie, Ibrahim, Ismail, Ibrahim, Kamil Zakwan, Mohd Azmi, Nor Azlina, Ab. Aziz, Nor Hidayati, Abd. Aziz, Mohd Saberi, Mohamad

    Published 2016
    “…Inspired by the estimation capability of Kalman filter, we have recently introduced a novel estimation-based optimization algorithm called simulated Kalman filter (SKF). …”
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  18. 18
    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation

    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

    Published 2022
    “…The proposed algorithm is simulated for simultaneous OPF-based conflicting objectives, respectively. …”
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  19. 19
    Predictive-reactive job shop scheduling for flexible production systems with the combination of optimization and simulation based algorithm

    Predictive-reactive job shop scheduling for flexible production systems with the combination of optimization and simulation based algorithm by Abdul Rahman, Azrul Azwan, Joe Yee, Tan, A Rahman, Muhamad Arfauz, Salleh, Mohd Rizal, Bilge, Pinar

    Published 2020
    “…This research will address some aspects of combining simulation and optimization-based algorithms for job-shop scheduling and rescheduling of flexible production systems. …”
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  20. 20
    Opposition-based learning simulated kalman filter for Numerical optimization problems

    Opposition-based learning simulated kalman filter for Numerical optimization problems by Mohd Falfazli, Mat Jusof

    Published 2016
    “…Simulated Kalman Filter (SKF) optimization algorithm is a population-based optimizer operated mainly based on Kalman filtering. …”
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