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  1. 1

    A high-performance democratic political algorithm for solving multi-objective optimal power flow problem by Ahmadipour M., Ali Z., Othman M.M., Bo R., Javadi M.S., Ridha H.M., Alrifaey M.

    Published 2025
    “…The proposed approach is tested and validated on IEEE 57-bus and IEEE 118-bus systems with different case studies. Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”
    Article
  2. 2

    Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions by Abdolrasol M.G.M., Jern Ker P., Hannan M.A., Tiong S.K., Ayob A., Almadani J.F.S.

    Published 2024
    “…Employing the Backtracking Search Algorithm (BSA), the research optimizes PI controller parameters to enhance system efficiency and reliability. …”
    Conference Paper
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  4. 4

    Optimal Location And Sizing Of Distrubuted Generator Using PSO And GA Algorithms In Power Systems by Hassan, Ayat Saleh

    Published 2019
    “…This research aimed to reduce total power losses and improve voltage profiles of the distribution system by proposing a practical swarm optimizion algorithm GA genetic algorithm to optimize DG size and location by taking into consideration increase number of DG units in the system. …”
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    Thesis
  5. 5

    A high-performance democratic political algorithm for solving multi-objective optimal power flow problem by Ahmadipour, Masoud, Ali, Zaipatimah, Othman, Muhammad Murtadha, Bo, Rui, Javadi, Mohammad Sadegh, Ridha, Hussein Mohammed, Alrifaey, Moath

    Published 2024
    “…The proposed approach is tested and validated on IEEE 57-bus and IEEE 118-bus systems with different case studies. Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”
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    Article
  6. 6

    Determining optimal location of static VAR compensator by means of genetic algorithm by Karami, Mahdi, Mariun, Norman, Ab Kadir, Mohd Zainal Abidin

    Published 2011
    “…The purpose of this paper is to study a practical and accurate heuristic method known as genetic algorithm (GA) which is used to find the optimal location of Static Var Compensator (SVC) and its appropriate size and setting. …”
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    Conference or Workshop Item
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    Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

    Published 2011
    “…In this research, we proposed optimal algorithms using Divide and Conquer, Brent’s theorem and parallel algorithms, appropriate for today’s large scale systems such as satellite processing systems, traffic control, weather forecasting which all face a large quantity of processing input data. …”
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    Thesis
  9. 9

    Multi-Objective Optimization of Solar Powered Irrigation System by Using Genetic Algorithm by Mohd Tholaat, Muhammad Ali Husaini

    Published 2015
    “…Thus, Genetic Algorithm is applied to solve multiple objective solar-irrigation system optimization. …”
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    Final Year Project
  10. 10

    Classical and metaheuristic optimizations performance in an electro-hydraulic control system by Chong, Chee Soon, Ghazali, Rozaimi, Chong, Shin Horng, Ghani, Muhammad Fadli, Md. Sam, Yahaya, Has, Zulfatman

    Published 2022
    “…A classical and metaheuristic optimization methods, which are gradient descent (GD) and particle swarm optimization (PSO) algorithm are used to obtaining the optimal gains of both controllers. …”
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    Article
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    AN UNFAIR SEMI-GREEDY REAL-TIME MULTIPROCESSOR SCHEDULING ALGORITHM. by ALHUSSIAN, HITHAM SEDDIG ALHASSAN

    Published 2014
    “…Optimal real-time multiprocessor scheduling algorithms always achieve higher processor utilization that is equal to the number of processors in the system. …”
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    Thesis
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    Two level Differential Evolution algorithms for ARMA parameters estimatio by Salami, Momoh Jimoh Emiyoka, Tijani, Ismaila, Aibinu, Abiodun Musa

    Published 2013
    “…The first level searches for the appropriate model order while the second level computes the optimal/sub-optimal corresponding parameters. The performance of the algorithm is evaluated using both simulated ARMA models and practical rotary motion system. …”
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    Proceeding Paper
  15. 15

    Alternative method for economic dispatch utilizing grey wolf optimizer by Wong, Lo Ing

    Published 2015
    “…Power system is one of the largest and most complex engineering systems created by human. …”
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    Thesis
  16. 16

    Monotone Fuzzy Rule Interpolation for Practical Modeling of the Zero-Order TSK Fuzzy Inference System by Kai Meng, Tay, Yi Wen, Kerk, Chee Peng, Lim

    Published 2022
    “…The proposed MFRI algorithm aims to achieve an ε -optimality condition and to produce an ε -optimal solution, which is geared for practical applications. …”
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    Article
  17. 17

    Backtracking search algorithm for optimal power dispatch in power system / Mostafa Modiri Delshad by Mostafa, Modiri Delshad

    Published 2016
    “…The goal is to determine the most optimal power sharing among the generating units in a power system. …”
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    Thesis
  18. 18

    Series division method based on PSO and FA to optimize Long-Term Hydro Generation Scheduling by Hammid, Ali Thaeer, M. H., Sulaiman

    Published 2018
    “…To deal with this complicated problem, Series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed in this paper. …”
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    Article
  19. 19

    Economic dispatch solution using moth-flame optimization algorithm by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Muhammad Ikram, Mohd Rashid, Hamdan, Daniyal

    Published 2018
    “…This paper proposes an application of a recent nature inspired optimization technique namely Moth-Flame Optimization (MFO) algorithm in solving the Economic Dispatch (ED) problem. …”
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    Conference or Workshop Item
  20. 20

    Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques by Hammid, Ali Thaeer

    Published 2018
    “…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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    Thesis