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  1. 1

    Bacterial foraging optimization algorithm for optimal load shedding in power systems / Wan Nur Eliana Afif Wan Afandie by Wan Afandie, Wan Nur Eliana Afif

    Published 2016
    “…By using Bacterial Foraging Optimization Algorithm (BFOA) technique, for each types of load shedding, the simulations are tested on IEEE 30-bus system for 3 and 5 load shedding locations. 3 different load conditions and one line outage cases are tested for 3 objective function and 3 multi-objective functions. …”
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    Thesis
  2. 2

    A novel peak load shaving algorithm for isolated microgrid using hybrid PV-BESS system by Rana, M.M., Romlie, M.F., Abdullah, M.F., Uddin, M., Sarkar, M.R.

    Published 2021
    “…To evaluate the effectiveness of the algorithm, simulation case studies have been conducted with actual load data and actual PV generation data. …”
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    Article
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    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

    Published 2022
    “…This thesis proposes and simulates the three novel optimization algorithms to handle DG allocation, different single-objective, and multi-objective OPF problems. …”
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    Thesis
  5. 5

    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
  6. 6

    Multi -Objective Economic Dispatch Using Evolutionary Programming by Noor Azlan Bin Adnan

    Published 2023
    “…The designated algorithm of MOEP used MATLAB to run the simulations. …”
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    Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method by Delgoshaei, Aidin

    Published 2016
    “…In this regard, 4 mathematical programming models are developed for forming cells and scheduling the materials on appropriate machines while the system costs are considered uncertain. Since the proposed models (like similar models in the literature) are likely to fall into local optimum points, a Branch and Bound based heuristic, a hybrid Simulated Annealing and Genetic algorithm, a hybrid Tabu search and Simulated Annealing, a hybrid Genetic algorithm and Simulated Annealing, a hybrid Ant Colony Optimization and Simulated Annealing and a hybrid Multi-layer Perceptron and Simulated Annealing algorithms are developed. …”
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    Thesis
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    Development of multi-objective optimization methods for integrated scheduling of handling equipment (AGVs, QCs, SP-AS/RS) in automated container terminals by Homayouni, Seyed Mahdi

    Published 2012
    “…Therefore, two meta-heuristic algorithms, namely genetic algorithm (GA) and simulated annealing (SA) algorithm, were developed to optimize the integrated scheduling of handling equipment. …”
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    Thesis
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    Techno-economic optimization and modelling of grid-connected photovoltaic and battery energy storage system by Gopinath Subramani

    Published 2023
    “…Optimization was performed via MATLAB using particle swarm optimization (PSO) and Genetic Algorithms (GA) techniques. …”
    text::Thesis
  13. 13

    Optimization of distributed generation using mix-integer optimization by genetic algorithm (MIOGA) Considering Load Growth by Che Muhamad Asad Safwan, Che Aziz, Norhafidzah, Mohd Saad, Mohammad Fadhil, Abas, Suliana, Ab Ghani, Ali, Abid

    Published 2022
    “…The results indicate that load growth has no effect on the optimal position, and only the optimal size of the DG unit is changed. …”
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    Conference or Workshop Item
  14. 14

    Load-Balancing Models for Scheduling Divisible Load on Large Scale Data Grids by Abduh Kaid, Monir Abdullah

    Published 2009
    “…In addition, the integration of the proposed DLT model with Simulated Annealing (SA) algorithm has been also developed. …”
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    Thesis
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    Long-term optimal planning of distributed generations and battery energy storage systems towards high integration of green energy considering uncertainty and demand response progra... by Ba-swaimi S., Verayiah R., Ramachandaramurthy V.K., ALAhmad A.K.

    Published 2025
    “…Scenario reduction through the Backward Reduction Algorithm (BRA) manages computational complexity. To solve the proposed model, a hybrid approach combining Non-Dominated Sorting Genetic Algorithm II (NSGAII) and Multi-Objective Particle Swarm Optimization (MOPSO) is employed. …”
    Article
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    Optimization of Distributed Generation Using Mix-Integer Optimization by Genetic Algorithm (MIOGA) Considering Load Growth by Safwan, C.M.A., Mohd Saad, N., Abas, M.F., Ab-Ghani, S., Ali, A.

    Published 2022
    “…The results indicate that load growth has no effect on the optimal position, and only the optimal size of the DG unit is changed. …”
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    Article
  19. 19

    Optimization of Distributed Generation Using Mix-Integer Optimization by Genetic Algorithm (MIOGA) Considering Load Growth by Safwan, C.M.A., Mohd Saad, N., Abas, M.F., Ab-Ghani, S., Ali, A.

    Published 2022
    “…The results indicate that load growth has no effect on the optimal position, and only the optimal size of the DG unit is changed. …”
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    Article
  20. 20

    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. …”
    Get full text
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    Article