Optimization of strutted beam parameters by A. K. Yusupov, H. M. Musеlеmov, T. O. Ustarhanov

“…The objective of the research is to design strutted beams that have optimal parameters for metal consumption.Methods. …”
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EEG channels selection for stroke patients rehabilitation using equilibrium optimizer by Al-Betar Mohammed Azmi, Alyasseri Zaid Abdi Alkareem, Makhadmeh Sharif Naser

“…This article addresses this problem by presenting an innovative optimization-based approach to the channel selection problem, employing a novel binary equilibrium optimizer (EO) as an optimization technique to identify the most relevant EEG channels. …”
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Improved PESA algorithm based on comentropy by Kun WANG, Lin-lin WANG, Yan LIU, Yu-hua ZHANG, Meng WU

“…Aiming at the issue that the computational effort the complexity and the running time of PESA algorithm are increasing rapidly with the growth of the solutions set number, a comentropy-based PESA algorithm (C-PESA) by merg-ing the entropy value metric into PESA algorithm was proposed. …”
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GAAOA-Lévy: a hybrid metaheuristic for optimized multilevel thresholding in image segmentation by Eman Mahmoud, Salem Alkhalaf, Tomonobu Senjyu, Masahiro Furukakoi, Ashraf Hemeida, Ghada Abozaid

“…However, multilevel thresholding, a widely used segmentation technique, suffers from high computational complexity due to the exhaustive search for optimal thresholds. This paper addresses this challenge by proposing a hybrid Genetic Algorithm-Archimedes Optimization Algorithm (GAAOA), further enhanced with a Lévy flight function (GAAOA-Lévy), to improve efficiency and accuracy in multilevel thresholding. …”
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Optimizing Trajectories for Rechargeable Agricultural Robots in Greenhouse Climatic Sensing Using Deep Reinforcement Learning with Proximal Policy Optimization Algorithm by Ashraf Sharifi, Sara Migliorini, Davide Quaglia

“…In this paper, we propose a method based on Deep Reinforcement Learning enriched with a Proximal Policy Optimization (PPO) algorithm for determining the best trajectory an agricultural robot must follow to balance the number of measurements and autonomy adequately. …”
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An Improved Multi-Objective Adaptive Human Learning Optimization Algorithm and Its Application in Optimizing Formulation Schemes for Rotary Hearth Furnaces by Jun Yao, Songcheng Zhou, Ling Wang, Xianxia Zhang

“…An improved multi-objective adaptive human learning optimization algorithm (IMOAHLO) is proposed, which enhances local optimization through neighborhood search and an adaptive learning mechanism. …”
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An efficient metaheuristic optimization algorithm for optimal power extraction from PV systems under various weather and load-changing conditions by Md.Al Imran Fahim, Md.Salah Uddin Yusuf, Monira Islam, Munshi Jawad Ibne Azad

“…To address these challenges, a new algorithm called horse herd optimization (HHO) has been applied to the maximum power point tracking (MPPT) controller. …”
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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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Application of GA-ACO Optimized BP Neural Network in Fault Diagnosis of Planetary Gearbox by Chang Gao, Zhongqing Yu, Qiang Zhou

“…Comparing the performance of ACO-BP neural network algorithm and GA-ACO-BP algorithm， the results show that the convergence speed of ACO Optimized BP neural network is slow and the recognition accuracy is not high， while GA-ACO-BP algorithm can accurately and quickly diagnose and identify the fault of planetary gearbox.…”
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A Hybrid Whale Optimization Approach for Fast-Convergence Global Optimization by Athanasios Koulianos, Antonios Litke, Nikolaos K. Papadakis

“…In this paper, we introduce the Levy Flight-enhanced Whale Optimization Algorithm with Tabu Search elements (LWOATS), an innovative hybrid optimization approach that enhances the standard Whale Optimization Algorithm (WOA) with advanced local search techniques and elite solution management to improve performance on global optimization problems. …”
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An improved dung beetle optimizer based on Padé approximation strategy for global optimization and feature selection by Tianbao Liu, Lingling Yang, Yue Li, Xiwen Qin

“…Feature selection is a crucial data processing method used to reduce dataset dimensionality while preserving key information. In this paper, we proposed a multi-strategy enhanced dung beetle optimization algorithm (mDBO) that integrates multiple strategies to effectively address the feature selection problem. …”
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Boosting feature selection efficiency with IMVO: Integrating MVO and mutation-based local search algorithms by Maryam Askari, Farid Khoshalhan, Hodjat Hamidi

“…In this research, we introduce the Improved Multi-Verse Optimizer (IMVO) algorithm, a novel feature selection method that integrates the Multi-Verse Optimizer (MVO) with local search algorithms (LSAs). …”
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Fuzzy Guiding of Roulette Selection in Evolutionary Algorithms by Krzysztof Pytel

“…The algorithm can be an effective tool in solving a wide range of optimization problems, for example, optimization of computer network infrastructure.…”
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Current-to-Best Crossover for Modified Jaya Algorithm by Sandeep Kumar Mogha, Sonal Deshwal, Pravesh Kumar

“…The Jaya algorithm is a recently designed metaheuristics and has been verified for its good performance in solving various engineering and scientific optimization applications. …”
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Mixed Multi-Strategy Improved Aquila Optimizer and Its Application in Path Planning by Tianyue Bao, Jiaxin Zhao, Yanchang Liu, Xusheng Guo, Tianshuo Chen

“…Traditional Aquila Optimizers, while effective, face limitations such as uneven population initialization, a tendency to get trapped in local optima, and slow convergence rates. …”
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Study on the probabilistic characteristics of forces in the support structure of heliostat array based on the DBO-BP algorithm by Haiyin Luo, Qiwei Xiong, Xuewen Zhang, Shi Zuo

“…Dung beetle optimization (DBO) algorithm is a metaheuristic algorithm mimicking dung beetle ball-rolling behavior, while Back propagation (BP) neural network is a feedforward artificial neural network trained via error backpropagation to adjust parameters. …”
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Investigation, Optimization of Energy Consumption and Yield Modeling of Two Paddy Cultivars with Genetic-Artificial Bee Colony Algorithm by S. Sharifi, N. Hafezi, M. H. Aghkhani

“…The results of the bee-genetic algorithm optimization revealed that the majority of the consumed resources could be effectively managed on the farm to closely match optimal conditions. …”
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Slope stability prediction under seismic loading based on the EO-LightGBM algorithm by Ning Ma, Ning Ma, Yuqi Zhang, Zaizhen Yao

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Ship Formation and Route Optimization Design Based on Improved PSO and D-P Algorithm by Peilong Xu, Dan Lan, Haolin Yang, Shengtian Zhang, Hyeonseok Kim, Incheol Shin

“…Based on this, a ship formation model combining improved particle swarm optimization algorithm and a generative route optimization method based on improved Douglas-Peucker algorithm are proposed. …”
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Optimization of Intelligent Maintenance System in Smart Factory Using State Space Search Algorithm by Nuttawan Thongtam, Sukree Sinthupinyo, Achara Chandrachai

“…By integrating with SSS algorithms, the IMS presents optimized maintenance cycle solutions to the maintenance manager, focusing on minimizing costs while maximizing the remaining lifetime of the equipment. …”
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