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  1. 1

    Integrated Grasshopper Algorithm-Evolutionary Programming Technique for Distributed Energy Resources Allocation by Kamalrolzaman M.A., Musirin I., Mansor M.H., Salimin R.H., Ismail N.L., Mohamed Kamari N.A.

    Published 2023
    “…Computer programming; Distributed computer systems; Electric power transmission; Electric power transmission networks; Energy resources; Evolutionary algorithms; Optimal systems; Distributed energy resource; Distributed Energy Resources; Distributed generation installation; Evolutionary programming techniques; Fitness; Objective functions; Optimisations; Optimization techniques; Power system networks; Resources allocation; Installation…”
    Conference Paper
  2. 2

    Integrated immune-commensal-evolutionary programming for economic dispatch and distributed generation installation / Mohd Helmi Mansor by Mansor, Mohd Helmi

    Published 2020
    “…EP is the leading optimizer of the hybrid algorithm while cloning operator of AIS and commensal operator of SOS are adopted into the EP algorithm to improve its performance. …”
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    Thesis
  3. 3

    Network reconfiguration and control for loss reduction using genetic algorithm by Jawad, Mohamed Hassan Izzaldeen

    Published 2010
    “…The methodology developed a combined optimization technique. Also capacitor placement employing Genetic Algorithm is presented in achieving the proper arrangement of capacitor in a distribution network. …”
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    Thesis
  4. 4

    Optimal multiple distributed generation output through rank evolutionary particle swarm optimization by Jamian, J.J., Mustafa, M.W., Mokhlis, Hazlie

    Published 2015
    “…Moreover, the local best (P-best) and global best (G(best)) values are obtained in simplify manner in the REPSO algorithm. The performance of this new algorithm will be compared to 3 well-known PSO methods, which are Conventional Particle Swarm Optimization (CPSO), Inertia Weight Particle Swarm Optimization (IWPSO), and Iteration Particle Swarm Optimization (IPSO) on 10 mathematical benchmark functions, and solving the optimal DG output problem. …”
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    Article
  5. 5

    An efficacious multi-objective fuzzy linear programming approach for optimal power flow considering distributed generation by Warid Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

    Published 2016
    “…An efficacious multi-objective fuzzy linear programming optimization (MFLP) algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG) effect. …”
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    Article
  6. 6

    Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain by Hussain, Muhamad Hatta

    Published 2020
    “…Thus, a reliable optimization technique such as Nature Inspired Metaheuristic Algorithms (NIMA) is crucial to address this issue. …”
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    Thesis
  7. 7

    Development of two matheuristics for production-inventory-distribution routing problem / Dicky Lim Teik Kyee by Dicky Lim , Teik Kyee

    Published 2018
    “…The aim of solving the model is to construct a production plan and delivery schedule which minimizes the overall costs while fulfilling customers’ demand over the planning horizon. We propose an optimization algorithm designed by the interpolation of metaheuristics and mathematical programming techniques, known as MatHeuristics algorithm, to solve the model. …”
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    Thesis
  8. 8

    Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin by Mat Yasin, Zuhaila

    Published 2014
    “…This thesis presents a new technique to determine the optimal locations and sizing of multiple DG units in a distribution system based on the concepts and principles of quantum mechanics in the Evolutionary Programming (EP) namely Quantum-Inspired Evolutionary Programming (QIEP). …”
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    Book Section
  9. 9

    Computational intelligence technique for DG installation within contingency scenario / Muhamad Saifullah Mahmud Affandi by Mahmud Affandi, Muhamad Saifullah

    Published 2014
    “…The Artificial Bee Colony (ABC) algorithm technique for solving the problem of optimal location and sizing of DG on distributed systems is presented. …”
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    Article
  10. 10

    Examination invigilation timetable using Genetic Algorithm / Mohamad Fakhrullah Ibrahim by Ibrahim, Mohamad Fakhrullah

    Published 2025
    “…GA employs key steps, including population initialization, fitness evaluation, selection, crossover, and mutation, to iteratively improve solutions. The fitness function in this system minimizes constraints such as invigilator availability, equitable workload distribution, and adherence to examination rules. …”
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  11. 11

    Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman by Azman, Alya Kauthar

    Published 2025
    “…This study applies Genetic Algorithms (GA) to optimize space distribution for test scheduling, addressing the challenge of managing multiple test sessions across distinct locations. …”
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    Thesis
  12. 12
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  14. 14

    Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin by Mat Yasin, Zuhaila

    Published 2014
    “…This thesis presents a new technique to determine the optimal locations and sizing of multiple DG units in a distribution system based on the concepts and principles of quantum mechanics in the Evolutionary Programming (EP) namely Quantum- Inspired Evolutionary Programming (QIEP). …”
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    Thesis
  15. 15

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

    Published 2019
    “…The rest sets of experiments carried out to evaluate the proposed algorithms. Precisely, the second set revealed that the proposed genetic medoid based algorithms with both DB and VRC fitness functions produced more accurate results compared with the genetic means based algorithms in terms of the Fscore. …”
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    Thesis
  16. 16

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…To evaluate the capability of ROA at addressing complicated problems, it has subjected to experiment several benchmark functions. The ROA has then compared with nine well-known optimization algorithms. …”
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    Thesis
  17. 17

    Two-stage strategic optimal planning of distributed generators and energy storage systems considering demand response program and network reconfiguration by Ba-swaimi S., Verayiah R., Ramachandaramurthy V.K., ALAhmad A.K., Padmanaban S.

    Published 2025
    “…The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is utilized to address the outer-stage optimization problem. …”
    Article
  18. 18

    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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    Thesis
  19. 19

    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
    “…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
  20. 20

    Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

    Published 2014
    “…The direct idea of making the conventional neural network learning algorithm more powerful towards outlying data is by replacing the mean square error (MSE) with a different symmetric and continuous cost function. …”
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