Investigation of technoeconomic optimization for sizing renewable energy systems using metaheuristic and hybrid algorithms by Bouafia Mohammed, El Fathi Amine, El Akchioui Nabil

“…This study focuses on optimizing grid-connected Hybrid Renewable Energy Systems (HRES) in Morocco using technoeconomic approaches, including metaheuristic algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Grey Wolf Optimization (GWO) and Artificial Bee Colony (ABC) and hybrid methods combining these latter with Modified Marquardt Gradient Descent (MGD). …”
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DESIGN HYBRID META-HEURISTIC APPROACHES FOR IMPROVED RELIABILITY OPTIMIZATION by Shakuntla Singla, Manisha Rani, Shilpa Rani, A. K. Lal

“…This study evaluates four metaheuristic methods for SRGM variable estimation: Gravitational Search Algorithm (GSA), Sine-Cosine Algorithm (SCA), Grey-Wolf Optimizer (GWO), and Regenerative Genetic Algorithm (RGA). …”
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Generic multidimensional economic environmental operation of power systems using equilibrium optimization algorithm by Mohamed T. Mouwafi, Adel A. Abou El-Ela, Amany A. El-Hamoly, Ragab A. El-Sehiemy

“…The numerical results obtained by the proposed EOA are compared with other optimization techniques such as grey wolf optimization, particle swarm optimization (PSO), differential evolution algorithm, and other optimization techniques in the literature. …”
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Innovative hybrid algorithm for efficient routing of limited capacity vehicles by Vu Hong Son Pham, Van Nam Nguyen, Nghiep Trinh Nguyen Dang

“…This study addresses the critical challenges posed by the capacitated vehicle routing problem (CVRP), particularly in the logistics of cement transportation under capacity constraints. Existing algorithms, including grey wolf optimizer (GWO) and whale optimization algorithm (WOA), exhibit significant limitations such as imbalanced exploration and exploitation, inefficiency in refining solutions, and inadequate adaptability to dynamic routing conditions. …”
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An energy-efficient routing protocol for wireless body area networks using hybrid artificial bee colony optimization and chicken swarm optimization algorithm by A. Dinesh, J. Rangaraj

“…The proposed work simulates a variety of scenarios to show the suggested algorithm’s superiority over Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), ABC, and Grey Wolf Optimization (GWO) protocols. …”
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Enhanced path planning algorithm via hybrid WOA-PSO for differential wheeled mobile robots by Huda Talib Najm, Nur Syazreen Ahmad, Ahmed Sabah Al-Araji

“…To validate the effectiveness of the proposed algorithm, its performance is evaluated across five diverse environments and compared against PSO, WOA, and Grey Wolf Optimization which is widely used for mobile robot path planning. …”
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Transformer Fault Diagnosis Based on Multi-Strategy Enhanced Dung Beetle Algorithm and Optimized SVM by Shuming Zhang, Hong Zhou

“…Experimental results demonstrate that the IDBO–SVM model attains accuracy improvements of 1.69%, 8.47%, and 10.17% over dung beetle optimization–SVM (DBO–SVM), sparrow search algorithm–SVM (SSA–SVM), and grey wolf optimization–SVM (GWO–SVM) models, respectively. …”
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GWO and WOA variable step MPPT algorithms-based PV system output power optimization by Abderrahim Zemmit, Abdelouadoud Loukriz, Khaled Belhouchet, Yahya Z. Alharthi, Muhannad Alshareef, Prabhu Paramasivam, Sherif S. M. Ghoneim

“…This study proposes two innovative Maximum Power Point Tracking (MPPT) algorithms based on the Whale Optimization Algorithm (WOA) and Grey Wolf Optimization (GWO). …”
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Meta-transformer: leveraging metaheuristic algorithms for agricultural commodity price forecasting by G. H. Harish Nayak, Md. Wasi Alam, B. Samuel Naik, B. S. Varshini, G. Avinash, Rajeev Ranjan Kumar, Mrinmoy Ray, K. N. Singh

“…To address these challenges, this study proposes a novel framework that combines Transformer models with Metaheuristic Algorithms (MHAs), including the Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO) to enhance agricultural price forecasting accuracy. …”
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Prediction of Interest Rate Using Artificial Neural Network and Novel Meta-Heuristic Algorithms by Milad Shahvaroughi Farahani

“…We used GA and a new algorithm called Grey Wolf Optimization, Particle Swarm Optimization (GWO-PSO) algorithm as a feature selection and choosing the best variables. …”
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Three-Dimensional Path Planning for Unmanned Aerial Vehicles Based on Hybrid Multi-Strategy Dung Beetle Optimization Algorithm by Hongmei Fei, Ruru Liu, Leilei Dong, Zhaohui Du, Xuening Liu, Tao Luo, Jie Zhou

“…To validate the effectiveness of HMSDBO, this study compares its performance with that of the Adaptive Chaotic Gray Wolf Optimization Algorithm (ACGWO), Primitive Dung Beetle Optimization Algorithm (DBO), Whale Optimization Algorithm (WOA), Crayfish Optimization Algorithm (COA), and Hyper-Heuristic Whale Optimization Algorithm (HHWOA) in complex agricultural UAV environments. …”
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An efficient enhanced exponential distribution optimizer: applications in global, engineering, and combinatorial optimization problems by Marwa M. Emam, Mohammed R. Saad, Mina Younan, Essam H. Houssein

“…The optimizers include the improved multi-operator differential evolution algorithm (IMODE), adaptive guided differential evolution algorithm (AGDE), whale optimization algorithm (WOA), grey wolf optimizer (GWO), sinh cosh optimizer (SCHO), RIME optimization algorithm (RIME), and the original EDO. …”
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A Hybrid Multi-Strategy Optimization Metaheuristic Algorithm for Multi-Level Thresholding Color Image Segmentation by Amir Seyyedabbasi

“…This study proposes a new hybrid multi-strategy metaheuristic algorithm named COSGO, which combines the strengths of grey wolf optimization (GWO) and Sand Cat Swarm Optimization (SCSO) to effectively address global optimization tasks. …”
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A study of scheduling strategies for microgrids based on the non-dominated sorting dung beetle optimization algorithm by Yutong Chen, Wu Ning, Wei Du

“…Specifically, compared with the Grey Wolf Optimizer (GWO) and the standard Dung Beetle Optimization (DBO) algorithm, the overall operation cost of NSDBO is reduced by 52% and 8.1%, respectively. …”
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Comparative Study of White Shark Optimization and Combined Meta-Heuristic Algorithm for Enhanced MPPT in Photovoltaic Systems by Fajar Kurnia Al Farisi, Zhi-Kai Fan, Kuo-Lung Lian

“…This paper proposes a novel hybrid metaheuristic algorithm (MHA) for maximum power point tracking (MPPT), integrating particle swarm optimization (PSO), the differential evolution algorithm (DEA), and the grey wolf optimizer (GWO). …”
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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm by Muhammad Shafiqul Islam, Mohd Ashraf Ahmad

“…Across all experiments, the IAOA-based method demonstrated superior performance compared to AOA and other methods, including a hybrid approach combining the average multi-verse optimizer and sine cosine algorithm, particle swarm optimizer, the sine cosine algorithm, multi-verse optimizer and grey wolf optimizer. …”
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Classification Prediction of Jujube Variety Based on Hyperspectral Imaging: A Comparative Study of Intelligent Optimization Algorithms by Quancheng Liu, Jun Zhou, Zhaoyi Wu, Didi Ma, Yuxuan Ma, Shuxiang Fan, Lei Yan

“…This study integrates hyperspectral imaging with intelligent optimization algorithms—Zebra Optimization Algorithm (ZOA), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO)—and a Support Vector Machine (SVM) model to classify jujube varieties. …”
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Towards efficient image segmentation: A fuzzy entropy-based approach using the snake optimizer algorithm by A. Tamilarasan, D. Rajamani

“…Extensive experiments were conducted on ten benchmark images, utilizing 2 to 5 thresholds, and comparing the performance of the SO algorithm against three state-of-the-art algorithms: Salp Swarm Algorithm (SSA), Grey Wolf Optimization (GWO), and Moth Flame Optimization (MFO).The results demonstrate that the SO algorithm consistently outperforms its counterparts across various metrics, achieving the highest average fitness values in 35 out of 40 attempts, with notable improvements in PSNR, SSIM, and FSIM. …”
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Optimization of Fuzzy Adaptive Logic Controller for Robot Manipulators Using Modified Greater Cane Rat Algorithm by Jian Sun, Shuyi Wu, Jinfu Chen, Xingjia Li, Ziyan Wu, Ruiting Xia, Wei Pan, Yan Zhang

“…For benchmarking, several state-of-the-art swarm intelligence algorithms—including particle swarm optimization (PSO), artificial bee colony (ABC), ant colony optimization (ACO), gray wolf optimization (GWO), covariance matrix adaptation evolution strategy (CMA-ES), adaptive guided differential evolution (AGDE), the basic greater cane rat algorithm (GCRA), and a trial-and-error method—are compared under identical conditions. …”
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Fluvial bedload transport modelling: advanced ensemble tree-based models or optimized deep learning algorithms? by Khabat Khosravi, Aitazaz A. Farooque, Sayed M. Bateni, Changhyun Jun, Dorsa Mohammadi, Zahra Kalantari, James R. Cooper

“…Using 926 datasets for 20 rivers, the performance of three groups of models was tested: (1) standalone tree-based models Alternating Model Tree (AMT) and Dual Perturb and Combine Tree (DPCT); (2) ensemble tree-based models Iterative Absolute Error Regression (IAER), ensembled with AMT and DPCT; and (3) optimized deep learning models Long Short-Term Memory (LSTM) and Recurrent Neural Network (RNN) ensembled with Grey Wolf Optimizer. …”
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