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  1. 61
  2. 62

    A GD-PSO Algorithm for Smart Transportation Supply Chain ABS Portfolio Optimization by Yingjia Sun, Hongfeng Ren

    Published 2021-01-01
    “…In this article, a penalty function based on graph density (GD) was introduced to the particle swarm optimization algorithm (PSO), and a GD-PSO algorithm was proposed. …”
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    Article
  3. 63

    Enhancing analogy-based software cost estimation using Grey Wolf Optimization algorithm by Taghi Javdani Gandomani, Maedeh Dashti, Sadegh Ansaripour, Hazura Zulzalil

    Published 2025-06-01
    “…Among the software estimation methods, analogy-based estimation (ABE) is one of the most popular ones. Although this method has been customized in recent years with the help of optimization algorithms to achieve better results, the use of more powerful optimization algorithms can be effective in achieving better results in software size estimation. …”
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  4. 64

    An effective parameter estimation on thermoelectric devices for power generation based on multiverse optimization algorithm by Luis Fernando Grisales-Noreña, Vanessa Botero-Gómez, Rubén Iván Bolaños, Faustino Moreno-Gamboa, Daniel Sanin-Villa

    Published 2025-03-01
    “…It achieves a minimum root mean square error of 0.001803 and a mean root mean square error of 0.001874 with a standard deviation equal to 3.013% over 1000 simulations. These results improve over those obtained by the Ant Lion Optimizer, which reported a minimum root mean square error of 0.001804 and a root mean square error of 0.001896 on average with a standard deviation of 3.788%.Additionally, the study highlights the efficiency of the Multiverse Optimization Algorithm in processing time, with an average execution time of 223.65 seconds. …”
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  5. 65

    Optimization Design Method of Pipe-Insulating Joints Based on Surrogate Model and Genetic Algorithm by Chen Guo, Zheng Yang, Jianbo Dong, Yanchao Yue, Linjun Tian, Ping Ma

    Published 2025-07-01
    “…This improves the computational efficiency of the optimization algorithm by establishing a surrogate model, which can be used to optimize the dimensions of insulation joints.…”
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  6. 66

    Magnetic targets positioning method based on multi-strategy improved Grey Wolf optimizer by Binjie Lu, Zongji Li, Xiaobing Zhang

    Published 2025-05-01
    “…Therefore, a Multi-Strategy Improved Grey Wolf Optimizer (MSIGWO) algorithm has been proposed to enhance the accuracy of magnetic target state estimation. …”
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    Article
  7. 67

    A design method of composite pixel-like antenna based on improved bald eagle search algorithm by WANG Yongqiang, LIU Bingqi, ZHU Bolin

    Published 2025-07-01
    “…This method not only retains the good convergence of the original algorithm, but also partially improves the global search ability. …”
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  8. 68

    Study on optimization of Al6061 sphere surface roughness in diamond turning based on central composite design model and grey wolf optimizer algorithms by Le Thanh Binh, Duong Xuan Bien, Ngo Viet Hung, Chu Anh My, Hoang Nghia Duc, Nguyen Kim Hung, Bui Kim Hoa

    Published 2025-02-01
    “…This paper presents optimization results of the Al6061 surface roughness in turning ultra-precision based on the central composite design method (CCD) and the grey wolf optimization algorithm (GWO). …”
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    Article
  9. 69

    Adaptive Particle Swarm Optimization with Landscape Learning for Global Optimization and Feature Selection by Khalil Abbal, Mohammed El-Amrani, Oussama Aoun, Youssef Benadada

    Published 2025-01-01
    “…Particle swarm optimization (PSO), an important solving method in the field of swarm intelligence, is recognized as one of the most effective metaheuristics for addressing optimization problems. …”
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  10. 70

    A multi-objective optimization-based ensemble neural network wind speed prediction model by Haoyuan Ma, Chang Liu, Ziyuan Qiao, Yuan Liang, Hongqing Wang

    Published 2025-09-01
    “…Built upon the NSGA-II framework, NS-ADPOA enhances offspring generation by leveraging a probabilistic error-driven fusion of Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA), combining their strengths in local and global search, respectively. …”
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  11. 71

    An intelligence technique for route distance minimization to store and marketize the crop using computational optimization algorithms by Saikat Banerjee, Abhoy Chand Mondal

    Published 2025-08-01
    “…The algorithm aims to find the most efficient path that includes all locations in a given set without revisiting any point. …”
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  12. 72

    Optimal Design of Short Fiber Bragg Grating Using Bat Algorithm With Adaptive Position Update by Ahmed Al-Muraeb, Hoda Abdel-Aty-Zohdy

    Published 2016-01-01
    “…We propose a new method to optimally design short triangular-spectrum fiber Bragg gratings (TS-FBGs), using the metaheuristic bat algorithm (BA). …”
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  13. 73

    VERIFICATION OF THE PARSEC METHOD AND OPTIMIZATION OF NACA-4412, SG-6043 USING GENETIC ALGORITHM IN MATLAB by Raheem Alhamdawee, M. Manzoor Hussain

    Published 2025-02-01
    “…The study also includes the improvement of the aerodynamic design of both airfoils through the use of a genetic algorithm which is coded and run in MATLAB, with the PARSEC parameters used as the base for optimization. …”
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  14. 74

    Multiscale Modeling and Reconstruction of Joint Motion: Finite Element Optimization Based on Particle Swarm Algorithm by Jiaju Zhu, Zhong Zhang, Runnan Liu, Meixue Ren, Guodong Ma

    Published 2025-01-01
    “…Additionally, iterative reconstruction decreased the error in the knee region by approximately 30% compared to non-iterative methods. The optimization process facilitated by the particle swarm algorithm revealed that most particles achieved high fitness levels after the initial iteration, and a considerable proportion shifted to the foreground region during the second iteration once fitness values dropped below 0.2. …”
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  16. 76

    Chaotic Mountain Gazelle Optimizer Improved by Multiple Oppositional-Based Learning Variants for Theoretical Thermal Design Optimization of Heat Exchangers Using Nanofluids by Oguz Emrah Turgut, Mustafa Asker, Hayrullah Bilgeran Yesiloz, Hadi Genceli, Mohammad AL-Rawi

    Published 2025-07-01
    “…This theoretical research study proposes a novel hybrid algorithm that integrates an improved quasi-dynamical oppositional learning mutation scheme into the Mountain Gazelle Optimization method, augmented with chaotic sequences, for the thermal and economical design of a shell-and-tube heat exchanger operating with nanofluids. …”
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  17. 77

    Feature Generation with Genetic Algorithms for Imagined Speech Electroencephalogram Signal Classification by Edgar Lara-Arellano, Andras Takacs, Saul Tovar-Arriaga, Juvenal Rodríguez-Reséndiz

    Published 2025-04-01
    “…This algorithm can efficiently explore ample feature space and identify the most relevant features for the task. …”
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  18. 78

    Optimizing Assembly Error Reduction in Wind Turbine Gearboxes Using Parallel Assembly Sequence Planning and Hybrid Particle Swarm-Bacteria Foraging Optimization Algorithm by Sydney Mutale, Yong Wang, De Tian

    Published 2025-07-01
    “…The methodology results in a 38% reduction in total assembly errors, improving both process accuracy and efficiency. Specifically, the PSBFO algorithm reduced errors from an initial value of 50 to a final value of 5 across 20 iterations, with components such as the low-speed shaft and planetary gear system showing the most substantial reductions. …”
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  19. 79

    A Hybrid Artificial Neural Network and Particle Swarm Optimization algorithm for Detecting COVID-19 Patients by Alla Ahmad Hassan, Tarik A Rashid

    Published 2021-12-01
    “…Following that, we implemented Neural Network and Particle Swarm Optimization algorithms. We used precision, accuracy score, recall, and F-Measure tests to evaluate the Neural Network with Particle Swarm Optimization algorithms. …”
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  20. 80

    Developing a Machine Learning-Driven Model that Leverages Meta-Heuristic Algorithms to Forecast the Load-Bearing Capacity of Piles by Tianhua Zhou

    Published 2023-12-01
    “…Additionally, it uses two separate meta-heuristic optimization methods, namely the Golden Jackal optimization algorithm (GJO) and Smell Agent Optimization (SAO), to achieve the best possible results. …”
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