A Comparison of the Black Hole Algorithm Against Conventional Training Strategies for Neural Networks by Péter Veres

“…This study presents a comparative analysis of four training algorithms, Backpropagation, Genetic Algorithm, Black-hole Algorithm, and Particle Swarm Optimization, evaluated across both classification and regression tasks. …”
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Enhancing workflow efficiency with a modified Firefly Algorithm for hybrid cloud edge environments by Deafallah Alsadie, Musleh Alsulami

“…In this study, we evaluate various scheduling algorithms, emphasizing the Modified Firefly Optimization Algorithm (ModFOA) and comparing it with established methods such as Ant Colony Optimization (ACO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). …”
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Enhancing Residential Electricity Consumption Forecasting with Meta-Heuristic Algorithms by Milad Mohebbi, Behnam Sobhani

“…The meta-heuristic algorithms employed for fine-tuning the ANN's weight and bias parameters include the Genetic Algorithm (GA), Multi-Verse Optimizer (MVO), Moth Flame Optimization (MFO), Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Advanced Grey Wolf Optimizer (AGWO), Biogeography-Based Optimization (BBO), and Particle Swarm Optimization with Grey Wolf Optimizer (PSOGWO). …”
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A multi-objective optimization algorithm-based capacity scheduling method for photovoltaic power hybrid energy storage systems by Shuaijie Wang, Xin Guan, Shu Liu

“…In this study, the combination of crossover algorithm and particle swarm optimization—crossover algorithm-particle swarm optimization (CS-PSO) algorithm—to optimize photovoltaic hybrid energy storage scheduling, improving global search and convergence speed, is discussed. …”
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Integrated Reliability Assessment and Optimal Reconfiguration of Islanded Microgrids Under Load Growth Using Fick’s Law Optimization Algorithm and Long Short-Term Memory Tec... by Hieu M. Pham, Duy C. Huynh, Loc D. Ho, Matthew W. Dunnigan, Corina Barbalata

“…To address the complex, mixed-variable nature of the reconfiguration problem, the Fick’s Law Optimization (FLO) algorithm is proposed. The FLO algorithm is compared with other metaheuristic algorithms such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO) algorithm, Non-dominated Sorting Genetic Algorithm II (NSGA-II), Artificial Bee Colony (ABC) algorithm, Grey Wolf Optimizer (GWO) algorithm, Equilibrium Optimizer (EO) algorithm, Runge-Kutta Optimizer (RUN) algorithm, and Honey Badger Algorithms (HBA) demonstrating superior performance in convergence speed, exploration–exploitation balance, and global optimality. …”
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Optimizing laser powder bed fusion parameters for enhanced hardness of Ti6Al4V alloys: A comparative analysis of metaheuristic algorithms for process parameter optimization by Praveenkumar V, Vijaykumar S. Jatti, Saiyathibrahim A, Praveen Kumar D, Murali Krishnan R, Vinaykumar S. Jatti, A. Johnson Santhosh

“…A comparative assessment of six metaheuristic algorithms, such as the JAYA algorithm, Cohort Intelligence (CI), Particle Swarm Optimization (PSO), Teaching-Learning-Based Optimization (TLBO), Genetic Algorithm (GA), and Simulated Annealing (SA), was performed for LPBF parameter optimization. …”
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A levy chaotic horizontal vertical crossover based artificial hummingbird algorithm for precise PEMFC parameter estimation by Pradeep Jangir, Absalom E. Ezugwu, Kashif Saleem, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Laith Abualigah

“…The combination of this method with PEMFC parameters results in a significantly improved performance compared to traditional methods, such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Grey Wolf Optimizer (GWO), and Sparrow Search Algorithm (SSA), which we use as baselines to validate PEMFC parameters. …”
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Multistep PV power forecasting using deep learning models and the reptile search algorithm by Sameer Al-Dahidi, Hussein Alahmer, Bilal Rinchi, Abdullah Bani-Abdullah, Mohammad Alrbai, Osama Ayadi, Loiy Al-Ghussain

“…Further, RSA was benchmarked against the Whale Optimization Algorithm (WOA), Gray Wolf Optimizer (GWO), and Constrained Particle Swarm Optimization (CPSO), and consistently outperformed all three across all models in both forecasting horizons. …”
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Maximizing Energy Output of Photovoltaic Systems: Hybrid PSO-GWO-CS Optimization Approach by Hassan S. Ahmed, Ahmed J. Abid, Adel A. Obed, Ameer L. Saleh, Reheel J. Hassoon

“…This study aims to address these challenges by combining cuckoo search (CS), gray wolf optimization (GWO), and particle swarm optimization (PSO) to enhance MPPT performance. …”
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Low Capillary Elastic Flow Model Optimization Using the Lattice Boltzmann Method and Non-Dominated Sorting Genetic Algorithm by Yaqi Hou, Wei Zhang, Jiahua Hu, Feiyu Gao, Xuexue Zong

“…The hyperparameters of the machine learning model are optimized using the particle swarm algorithm. In contrast, the non-dominated sorting genetic algorithm (NSGA-II) is incorporated to optimize bubble lengths and stability. …”
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Coverage optimization of wireless sensor network utilizing an improved CS with multi-strategies by Sen-Yu Yang, Chang-Feng Chen, Kai-Qing Zhou, Yun Ou

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A novel pigeon-inspired optimization with QUasi-Affine TRansformation evolutionary algorithm for DV-Hop in wireless sensor networks by Xiao-Xue Sun, Jeng-Shyang Pan, Shu-Chuan Chu, Pei Hu, Ai-Qing Tian

“…According to the experimental results, they demonstrate that it is more outstanding than the Pigeon-Inspired Optimization algorithm, the QUasi-Affine TRansformation Evolutionary algorithm, and particle swarm optimization algorithm. …”
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Flow Control of Tractor Multi-Channel Hydraulic Tester Based on AMESim and PSO-Optimized Fuzzy-PID by Qinglun Li, Xuefeng Bai, Yang Lu, Xiaoting Deng, Zhixiong Lu

“…To improve the dynamic response, linearity, and control accuracy of the YYSCT-250-3 tractor multi-circuit hydraulic output power tester, this study develops a particle swarm optimization (PSO)-tuned fuzzy-proportional–integral–derivative (Fuzzy-PID) control strategy. …”
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Design of low-carbon planning model for vehicle path based on adaptive multi-strategy ant colony optimization algorithm by Qi Guo, Rui Li, Changjiang Zheng, Gwanggil Jeon

“…Moreover, comparative analyses of various optimization methods on the custom-built dataset reveal that the ant colony optimization algorithm markedly outperforms the simulated annealing algorithm (SA) and particle swarm optimization algorithm (PSO). …”
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Large Data Oriented to Image Information Fusion Spark and Improved Fruit Fly Optimization Based on the Density Clustering Algorithm by Yanfang Zhang

“…Then, a hybrid fruit fly particle swarm algorithm based on a genetic optimization mechanism is proposed to achieve dynamic optimization seeking for parameters in local clustering to improve the clustering effect of local clustering. …”
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Optimal Allocation of Hybrid Renewable Distributed Generation with Battery Energy Storage System Using MOEA/D-DRA Algorithm by P. Pon Ragothama Priya, S. Baskar, S. Tamil Selvi, C. K. Babulal

“…Simulation studies are conducted on IEEE 33-node and TNEB 84-node Radial Distribution Systems (RDSs), comparing results with the Rider Optimization Algorithm (ROA) and Hybrid Nelder Mead-Particle Swarm Optimization (HNMPSO) respectively. …”
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Ultrahigh-Dimensional Model and Optimization Algorithm for Resource Allocation in Large-Scale Intelligent D2D Communication System by Minxin Liang, Jiandong Liu, Jinrui Tang, Ruoli Tang

“…In addition, a novel evolutionary algorithm called the cooperatively coevolving particle swarm optimization with variable-grouping (VGCC-PSO) is developed, in which a novel mutation operation is introduced for ensuring fast satisfaction of constraints. …”
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Research on the Optimization Method of Visual Sensor Calibration Combining Convex Lens Imaging with the Bionic Algorithm of Wolf Pack Predation by Qingdong Wu, Jijun Miao, Zhaohui Liu, Jiaxiu Chang

“…The comparative experimental results show that the average reprojection errors of the simulated annealing algorithm, Zhang’s calibration method, the sparrow search algorithm, the particle swarm optimization algorithm, bionic algorithm of Wolf Pack Predation, and the algorithm proposed in this paper (CLI-WPP) are 0.42986500, 0.28847656, 0.23543161, 0.219342495, 0.10637477, and 0.06615037, respectively. …”
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Optimization of electric vehicle charging facility layout considering the enhancement of renewable energy consumption capacity and improvement of PSO algorithm by Di Zheng, Baobao Zheng

“…To deal with the optimization model, the particle swarm optimization is adopted and improved in three aspects. …”
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TCN-LSTM-MHSA model optimized by improved slime mould algorithm for stress prediction of roadway anchor bolts (cables) by QI Junyan, CHE Yuhao, WANG Lei, YUAN Ruifu

“…Experimental results showed that: ① Compared with the Slime Mould Algorithm (SMA), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Sparrow Search Algorithm (SSA), the ISMA optimization strategy demonstrated better convergence speed and optimization ability in multiple benchmark function tests. ② In the stress prediction experiment, ablation experiments verified the necessity of TCN, LSTM, and MHSA modules. ③ The ISMA-optimized TCN-LSTM-MHSA model outperformed mainstream prediction models such as BP and GRU in MAE, RMSE, and R2 metrics, showing higher prediction accuracy and stability.…”
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