A Hybrid Approach Incorporating WSO-HO and the Newton-Raphson Method to Enhancing Photovoltaic Solar Model Parameters Optimisation by Jeridi Ahmed, Moulahi Mohamed Hedi, Khaterchi Hechmi, Zaafouri Abderrahmen

“…Accurate parameter estimation is vital for optimising the performance and design of photovoltaic (PV) systems. While metaheuristic algorithms (MHAs) offer promising solutions, they often face challenges such as slow convergence and difficulty balancing exploration and exploitation. …”
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Collaborative Optimization of Model Pruning and Knowledge Distillation for Efficient and Lightweight Multi-Behavior Recognition in Piglets by Yizhi Luo, Kai Lin, Zixuan Xiao, Yuankai Chen, Chen Yang, Deqin Xiao

“…In the first stage, the LAMP pruning algorithm is used to prune and optimize redundant channels, resulting in the lightweight YOLOv8-Prune. …”
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Improving air quality prediction using hybrid BPSO with BWAO for feature selection and hyperparameters optimization by Mohamed S. Sawah, Hela Elmannai, Alaa A. El-Bary, Kh. Lotfy, Osama E. Sheta

“…Feature selection (FS) was conducted using Binary version of Grey Wolf Optimizer (BGWO), Particle Swarm Optimization (BPSO), Whale Optimization Algorithm (BWAO), and a novel hybrid BPSO-BWAO approach to identify the most relevant features for AQI prediction. …”
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Advanced Optimization of Flowshop Scheduling with Maintenance, Learning and Deteriorating Effects Leveraging Surrogate Modeling Approaches by Nesrine Touafek, Fatima Benbouzid-Si Tayeb, Asma Ladj, Riyadh Baghdadi

“…We develop and evaluate two distinct strategies for integrating surrogate modeling into the optimization process, leveraging the ABC algorithm. The first strategy uses a Kriging model to dynamically guide the selection of the most effective search operator at each stage of the employed bee phase. …”
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An efficient binary spider wasp optimizer for multi-dimensional knapsack instances: experimental validation and analysis by Mohamed Abdel-Basset, Reda Mohamed, Karam M. Sallam, Ibrahim Alrashdi, Ibrahim A. Hameed

“…The usefulness and efficiency of the proposed algorithms are also demonstrated by comparing both of them to several metaheuristic optimizers in terms of some performance criteria. …”
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Multi-objective optimization of cushion gas design in underground gas storage using machine learning by Mohaddeseh Ahmadi Aghdam, Maryam Fazaeli, Mahdi Kanaani, Behnam Sedaee

“…This model enabled rapid multi-objective optimization using the MOPSO algorithm. Several Pareto fronts were generated, and the best front provided 500 optimal solutions after 300 iterations. …”
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Optimizing Superior Seed Bunches: A New Approach to Artificial Pollination with Machine Learning Models by Yabani Yabani, Retna Astuti Kuswardani

“… This study aims to optimize oil palm production through the application of more targeted pollination techniques using a data-driven approach and a new optimization model. …”
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Optimizing net-zero energy strategies in airports through a hybrid multi-method framework by Filiz Mizrak, Kagan Cenk Mizrak, Turhan Karakaya

“…The proposed model integrates the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) for generating Pareto-optimal solutions, K-Means clustering for classifying strategies, and the Pythagorean Fuzzy Analytic Hierarchy Process (PFAHP) for prioritizing alternatives under uncertainty. …”
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Optimization Design Scheme for Aerodynamic Noise Reduction in Pantograph Area of High-speed Railway EMU by YU Yongge, WANG Chengtao, GAO Yang, YU Wanyi, MA Changfu, ZHANG Guoqin

“…［Result & Conclusion］ Scheme 4 is identified as the optimal solution. When applied to the CR400BF EMU operating at a speed of 350 km/h, the overall train radiated noise sound pressure level at the nearest standard measuring point to the pantograph is reduced by 0.99 dB(A), while the radiated noise sound pressure level in the pantograph area is reduced by 1.70 dB(A). …”
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A cluster-optimized regulation method for distribution networks considering distributed photovoltaic heterogeneous characteristics by Junhao Li, Xin Wang, Qi Guo, Chunzhi Yang, Yizhe Chen, Ruifeng Zhao, Ming Li

“…To address these challenges, a cluster-optimized regulation method is proposed, leveraging DPV heterogeneity to enable coordinated regulation while reducing directly-managed devices through DN clustering. …”
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Optimization of Urban Rail Transit Train Stock Utilization under Re-coupling Operation Mode by DENG Chengyuan, LU Jinsheng, ZHU Changfeng, SUN Yuanguang, MA Bin

“…［Objective］ Re-coupling operation mode can effectively improve the matching degree between the passenger flow and the transport capacity of urban rail transit, while it also poses challenges to the formulation of the train stock utilization plan. …”
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Robust personalized pricing under uncertainty of purchase probabilities by Shunnosuke Ikeda, Naoki Nishimura, Noriyoshi Sukegawa, Yuichi Takano

“…Experimental results demonstrate the effectiveness of our robust optimization model and highlight the utility of our Lagrangian decomposition algorithm in terms of both computational efficiency and solution quality.…”
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Experimental Study on Compressive Capacity Behavior of Helical Anchors in Aeolian Sand and Optimization of Design Methods by Qingsheng Chen, Wei Liu, Linhe Li, Yijin Wu, Yi Zhang, Songzhao Qu, Yue Zhang, Fei Liu, Yonghua Guo

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AI-driven generative and reinforcement learning for mechanical optimization of 2D patterned hollow structures by Yicheng Shan, Leitao Cao, Yu Wang, Jing Ren, Chen Huang, Wenli Gao, Shengjie Ling

“…In this study, we develop an integrated framework combining conditional generative adversarial networks (cGANs) and deep Q-networks (DQNs) to predict and optimize the stress fields of 2D-PHS. We generated a comprehensive dataet comprising 1000 samples across five distinct density classes using a custom grid pattern generation algorithm, ensuring a wide range of structural variations. …”
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Human-in-the-Loop Optimization of the Stiffness and Alignment of a Prosthetic Foot to Reduce the Metabolic Cost of Walking by Thijs Tankink, Han Houdijk, Johnnidel Tabucol, Marco Leopaldi, Juha M. Hijmans, Raffaella Carloni

“…We aimed to minimize the metabolic cost of walking by optimizing the stiffness and alignment of the prosthetic foot, using an evolutionary optimization algorithm. …”
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Greening concept in inventory system for deteriorating items with preservation investment and price and stock dependent demand via marine predators algorithm by Hachen Ali, Gobinda Chandra Panda, Adel Fahad Alrasheedi, Ali Akbar Shaikh, Jeonghwan Gwak

“…To solve it efficiently, this study employs the Marine Predators Algorithm (MPA)—a newly developed metaheuristic algorithm well-suited for continuous, nonlinear optimization. …”
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A New Computer-Aided Diagnosis System for Breast Cancer Detection from Thermograms Using Metaheuristic Algorithms and Explainable AI by Hanane Dihmani, Abdelmajid Bousselham, Omar Bouattane

“…To achieve these goals, we proposed a new multi-objective optimization approach named the Hybrid Particle Swarm Optimization algorithm (HPSO) and Hybrid Spider Monkey Optimization algorithm (HSMO). …”
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A Hierarchical Control Algorithm for a Pursuit–Evasion Game Based on Fuzzy Actor–Critic Learning and Model Predictive Control by Penglin Hu, Chunhui Zhao, Quan Pan

“…FACL is used for perception, decision-making, and predicting the trajectories of agents, while MPC is utilized to address the flight control and target optimization of quadrotors. …”
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An improved hybrid artificial bee colony algorithm for a multi-supplier closed-loop location inventory problem with customer returns. by Hao Guo, Xiaomei Lai, Ju Guo, Ge You, Ibrahim Alnafrah

“…The results of numerical experiments demonstrate that IHABC consistently outperforms competing methods, achieving superior solutions with the lowest mean values and optimal total cost results, while also requiring less computation time. …”
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Delay margin analysis of FOTID controller for RES based EV system using MMGPE optimization by Adhit Roy, Susanta Dutta, Soumen Biswas, Anagha Bhattacharya, Sajjan Kumar, Soham Dutta, Provas Kumar Roy

“…Since the behaviour of solar and wind generation changes quickly with the environment and causes significant synchronizing imbalances between various units with system delays in large electrical grids, users face numerous challenges while shifting from conventional energy to renewable energy. …”
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