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  1. 21

    Energy Efficiency and Reliability in Underwater Wireless Sensor Networks Using Cuckoo Optimizer Algorithm by M. Dosaranian-Moghadam, Z. Amo-Rahimi

    Published 2018-06-01
    “…In the proposed algorithm, by presenting a cost function in COA algorithm, a hop-by-hop method of route selection is performed using power consumption and energy content of the current node; while in Greedy Geographic Forwarding based on Geospatial Division (GGFGD) algorithm, data transfer is based on the closest route to a destination criterion. …”
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  2. 22

    Artificial Optimizer Algorithm for Power System Stabilizer design problem and multidisciplinary engineering applications by Narinder Singh, Mandeep Kaur, Essam H. Houssein

    Published 2024-11-01
    “…The novelty of this research lies in presenting a fresh stochastic algorithm enthused via ‘Velociraptor’ social intelligence in wildlife (or nature), known as the Velociraptor Group Optimization algorithm (VROA). …”
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  3. 23

    Diesel Engine Urea Injection Optimization Based on the Crested Porcupine Optimizer and Genetic Algorithm by Xu Chen, Changhai Ma, Quanli Dou, Shuzhan Bai, Ke Sun, Zhenguo Li

    Published 2025-05-01
    “…Finally, the Nondominated Sorting Genetic Algorithm II (NSGA-II) was used to optimize the urea injection volume for all conditions. …”
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  4. 24

    Reliability growth model of quantum direct current electricity meter software based on optimization network by TIAN Teng, QIU Rujia, ZHAO Long, GENG Jiaqi, WANG Enhui, SUN Yu

    Published 2025-03-01
    “…In this paper, we will replace the training process of the neural network with a parameter optimization process, and use the improved whole annealing genetic algorithm (WAGA) to optimize the parameters of the back propagation neural network. …”
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    Optimal PID controller with evolutionary optimization algorithms for rehabilitation robots by Kamran Joyo, Talha Ahmed Khan, Kushsairy Abdul Kadir, Mohd Nizam Bin Husen, Haidawati Mohamad Nasir, Munaza Azhar

    Published 2025-07-01
    “…The Firefly algorithm also delivered promising results, achieving the shortest rise time (0.689 s) and a quick settling time (1.08 s), while keeping the overshoot (4.45%) nearly on par with PSO. …”
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  7. 27

    Statistical Analysis Method for Optimal Prameters of Telemetry Communication by XIE Jun, WU Sailong, HAO Hang, ZHANG Songwei, WU Ruiqing, SUN Xiangyang

    Published 2025-06-01
    “…In addition, the proposed method completes a parameter optimization time of merely 0.08 seconds when processing 350 000 logging data points, demonstrating significant superiority over the existing optimization method based on machine learning and genetic algorithm. …”
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  8. 28

    Sigmoid-Function-Based Adaptive Pelican Optimization Algorithm for Global Optimization by A. F. S. Yussif, S. Adjei, B. E. Wilson

    Published 2025-03-01
    “… This paper introduces the Sigmoid-function-based Adaptive Pelican Optimization Algorithm (MPOA), an enhanced version of the traditional Pelican Optimization Algorithm (POA) aimed at improving the POA's performance. …”
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  9. 29

    SOMO-m Optimization Algorithm with Multiple Winners by Wei Wu, Atlas Khan

    Published 2012-01-01
    “…More importantly, SOMO-m algorithm with m≥2 can be used to find two or more minimums simultaneously in a single learning iteration process, while the original SOM-based optimization (SOMO) algorithm has to fulfil the same task much less efficiently by restarting the learning iteration process twice or more times.…”
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  10. 30

    Metaheuristic Algorithms for Optimization: A Brief Review by Vinita Tomar, Mamta Bansal, Pooja Singh

    Published 2024-03-01
    “…In the area of optimization, metaheuristic algorithms have attracted a lot of interest. …”
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    Comprehensive Research on Energy Saving Synergy Optimization and Optimal Real-time Control of Hybrid Electric Mining Trucks by Li Hongliang, Zhang Guojing, Fan Ping

    Published 2024-07-01
    “…This study takes the hybrid electric mining truck as a research object, establishes the mathematical model of the whole vehicle, takes reducing fuel consumption as the goal, establishes a collaborative optimization model that comprehensively considers the interaction between transmission system parameters and energy management strategies, and combines particle swarm optimization (PSO) algorithm and dynamic programming (DP) algorithm to build a two-layer interactive optimization algorithm to eliminate the interaction between transmission system parameters and energy management strategies. …”
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  13. 33

    An effective feature selection approach based on hybrid Grey Wolf Optimizer and Genetic Algorithm for hyperspectral image by Yiqun Shang, Minrui Zheng, Jiayang Li, Xinqi Zheng

    Published 2025-01-01
    “…To address these challenges, we propose GWOGA, a novel hybrid algorithm that combines Grey Wolf Optimizer (GWO) and Genetic Algorithm (GA), aiming to achieve an effective balance between exploration and exploitation. …”
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  14. 34

    Enhanced optimisation of MPLS network traffic using a novel adjustable Bat algorithm with loudness optimizer by Mohsin Masood, Mohamed Mostafa Fouad, Rashid Kamal, Khursheed Aurangzeb, Sheraz Aslam, Zahid Ullah, Ivan Glesk

    Published 2025-06-01
    “…This study explores the influence of the algorithm's loudness parameter and introduces a novel Adjustable Bat Algorithm (ABAT) that dynamically optimizes this parameter. …”
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    Hierarchical multi step Gray Wolf optimization algorithm for energy systems optimization by Idriss Dagal, AL-Wesabi Ibrahim, Ambe Harrison, Wulfran Fendzi Mbasso, Ahmad O. Hourani, Ievgen Zaitsev

    Published 2025-03-01
    “…Abstract Gray Wolf Optimization (GWO), inspired by the social hierarchy and cooperative hunting behavior of gray wolves, is a widely used metaheuristic algorithm for solving complex optimization problems in various domains, including engineering design, image processing, and machine learning. …”
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  18. 38

    Application of Artificial Intelligence Computer Intelligent Heuristic Search Algorithm by Fanghai Gong

    Published 2022-01-01
    “…After 114 iterations of the heuristic search algorithm, the optimal value is 6.83353635e-001, while the average optimal value is 6.83551939e-001. …”
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  19. 39

    Improved grey wolf optimization algorithm based service function chain mapping algorithm by Yue ZHANG, Junnan ZHANG, Xiaochun WU, Chen HONG, Jingjing ZHOU

    Published 2022-11-01
    “…With the rise of new Internet applications such as the industrial Internet, the Internet of vehicles, and the metaverse, the network’s requirements for low latency, reliability, security, and certainty are facing severe challenges.In the process of virtual network deployment, when using network function virtualization technology, there were problems such as low service function chain mapping efficiency and high deployment resource overhead.The node activation cost and instantiation cost was jointly considered, an integer linear programming model with the optimization goal of minimizing the average deployment network cost was established, and an improved grey wolf optimization service function chain mapping (IMGWO-SFCM) algorithm was proposed.Three strategies: mapping scheme search based on acyclic KSP algorithm, mapping scheme coding and improvement based on reverse learning and nonlinear convergence were added to the standard grey wolf optimization algorithm to form this algorithm.The global search and local search capabilities were well balanced and the service function chain mapping scheme was quickly determined by IMGWO-SFCM.Compared with the comparison algorithm, IMGWO-SFCM reduces the average deployment network cost by 11.86% while ensuring a higher service function chain request acceptance rate.…”
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  20. 40

    Chain hybrid feature selection algorithm based on improved Grey Wolf Optimization algorithm. by Xiaotong Bai, Yuefeng Zheng, Yang Lu, Yongtao Shi

    Published 2024-01-01
    “…In particular, the wrapper algorithm is an improved Grey Wolf Optimization (IGWO) algorithm based on random disturbance factors, while the parameters are adjusted to vary randomly to make the population variations rich in diversity. …”
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