A novel two stage neighborhood search for flexible job shop scheduling problem considering reconfigurable machine tools by Yanjun Shi, Chengjia Yu, Shiduo Ning

“…This paper focuses on the flexible job shop scheduling problem with machine reconfigurations (FJSP-MR) and proposes an improved genetic algorithm with a two-stage neighborhood search (IGA-TNS) to minimize total weighted tardiness (TWT). …”
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The prediction of karst-collapse susceptibility levels based on the ISSA-ELM integrated model by Jiaxin Wang, Ying Yang, Xian Yang, Yulong Lu, Yang Liu, Da Hu, Yongjia Hu

“…To address the limitations of conventional prediction methods, in this study, we introduce an enhanced predictive model, the improved sparrow search algorithm-optimized extreme learning machine (ISSA-ELM), for accurate karst-collapse susceptibility assessment. …”
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Designing High‐Performance, Manufacturing‐Friendly Rotor Blades for Micro Wind Turbines via Cambered Plate Airfoil Optimization by Moritz Burmester, Abdullah Khisraw, Peter Dalhoff

“…This research highlights the potential of cambered plate airfoils to improve micro wind turbine performance while maintaining ease of manufacturing, with potential applications in unmanned aerial vehicles (UAVs), drone propellers, and ventilation systems. …”
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A Dual-Strategy Framework for Cyber Threat Detection in Imbalanced, High-Dimensional Data Across Heterogeneous Networks by T. Saranya, S. Indra Priyadharshini

“…Second, the Cauchy-Gaussian Genetic-Arithmetic Optimizer (CG-GAO) addresses the challenge of high-dimensional data by combining a genetic algorithm (GA) and an arithmetic optimization algorithm (AOA), enhancing exploration and preventing premature convergence. …”
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Hybrid FOT2F-FOPD controller for permanent magnet synchronization motor based on ILA optimization with SRF-PLL by Mohamed Nouh, Belal A. Zalam, Amged Sayed

“…Then, the controller parameters (gain, μ and λ) are tuned based on a novel optimization algorithm called Incomprehensible but Intelligible-in-time (IbI) Logics algorithm (ILA). …”
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Intelligent design of high-performance fluids for thermal management: integrating response surface methodology, weighted Tchebycheff method, and strength Pareto evolutionary algori... by Mohamed Bechir Ben Hamida, Ali Basem, Neeraj Varshney, Loghman Mostafa

“…This study presents a novel multi-objective optimization framework integrating response surface methodology (RSM) with enhanced hill climbing (EHC) algorithm and strength Pareto evolutionary algorithm II (SPEA-II) to optimize multiple TPPs. …”
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Advanced removal of butylparaben from aqueous solutions using magnetic molybdenum disulfide nanocomposite modified with chitosan/beta-cyclodextrin and parametric evaluation through... by Saeed Hosseinpour, Alieh Rezagholizade-shirvan, Mohammad Golaki, Amir Mohammadi, Amir Sheikhmohammadi, Zahra Atafar

“…Butylparaben extraction performance reaches its maximum level while resource utilization improves throughout the entire extraction technique under the established optimal conditions. …”
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Energy optimization through morphing blade design under structural constraints: a case study on the NREL 1.5 MW wind turbine by Najafian Arezoo, Jahangirian Alireza

“…The morphing process is modeled using an m-degree shape function and optimized through a Genetic Algorithm (GA) to maximize power generation while minimizing structural displacement and thrust forces. …”
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Facility location problem for senior centers in an upcoming super-aging society by Eun Hak Lee, Jonghwa Jeong

“…This study aims to address the facility location problem for senior centers in upcoming super-aging societies. An optimization model is developed using a genetic algorithm to determine the optimal locations of senior centers. …”
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Optimal Driving Torque Control Strategy for Front and Rear Independently Driven Electric Vehicles Based on Online Real-Time Model Predictive Control by Hang Yin, Chao Ma, Haifeng Wang, Zhihao Sun, Kun Yang

“…To enable online real-time implementation, an improved sparrow search algorithm (SSA) is designed. …”
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Optimized Dual-Battery System with Intelligent Auto-Switching for Reliable Soil Nutrient Monitoring in Remote IoT Applications by Doan Perdana, Pascal Lorenz, Bagus Aditya

“…The experimental results reveal distinct performance improvements. A baseline single-battery system sustains 28 h of operation with 31.2% average reliability, while a conventional dual-battery configuration extends operation to 45 h with 42.6% reliability. …”
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The open-closed mod-minimizer algorithm by Ragnar Groot Koerkamp, Daniel Liu, Giulio Ermanno Pibiri

“…This new method—the open-closed minimizer—offers improved density for small $$k \le w$$ k ≤ w while being as fast to compute as the random minimizer. …”
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A hybrid machine learning algorithm approach to predictive maintenance tasks: A comparison with machine learning algorithms by Jorge Paredes, Danilo Chávez, Ramiro Isa-Jara, Diego Vargas

“…However, there is room for improvement in this prediction. In this paper, a hybrid approach that combines supervised learning (multi-layer perceptron MLP) and reinforcement learning (Q-learning) algorithms is proposed with the aim of improving the accuracy and precision of predicting the RUL. …”
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An Effective Genetic Algorithm for Mixed Precision by Wanyu Zhang, Yu Shang, Min Tsao, Yiwei Li, Xiaoyu Song

“…Addressing this trade-off is essential for optimizing performance while ensuring numerical accuracy. …”
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Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction by DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en

“…[Conclusions](1) The MVMD decomposition method can control the number of decomposition layers, ensuring complete signal feature extraction without overfitting while improving processing speed.(2) Pearson correlation coefficient method enhances prediction accuracy through decomposed data classification.(3) The MEA-BP can improve signal-to-noise ratio, adapt to complex environments, enhance learning efficiency and generalization ability, and reduce computational complexity.(4) The GWO-ELM algorithm integrates grey wolf optimizer with extreme learning machine, providing a fast and adaptive solution for time-series prediction with reduced overfitting and improved efficiency.(5) The overall combined model can efficiently and stably process large amount of data while ensuring high accuracy.…”
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PERFORMANCE PREDICTION OF ROADHEADERS USING SUPPORT VECTOR MACHINE (SVM), FIREFLY ALGORITHM (FA) AND BAT ALGORITHM (BA) by Arash Ebrahimabadi, Alireza Afradi

“…It can be concluded that while predictive models produce satisfactory results, the Bat Algorithm (BA) demonstrates a higher level of precision and realism in its outcomes.…”
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A novel Parrot Optimizer for robust and scalable PEMFC parameter optimization by Mohammad Aljaidi, Pradeep Jangir, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, Gulothungan G., Ali Fayez Alkoradees, Mohammad Khishe, Reena Jangid

“…I–V and V–P characteristic simulations match experimental results across different temperature and pressure values which proves the theoretical value and practical usage of PO in solving nonlinear optimization problems. The study demonstrates PO as a dependable optimization method which improves PEMFC design processes while enhancing operational reliability through future research that includes real-time control and algorithm combination and system scalability.…”
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Efficient Frequency Management for Hybrid AC/DC Power Systems Based on an Optimized Fuzzy Cascaded PI−PD Controller by Awadh Ba Wazir, Sultan Alghamdi, Abdulraheem Alobaidi, Abdullah Ali Alhussainy, Ahmad H. Milyani

“…The SBOA-FCPIPD controller’s ITAE value is 0.5101, while sine cosine adopted an improved equilibrium optimization algorithm-based adaptive type 2 fuzzy PID controller and obtained 4.3142. …”
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A novel Probabilistic Bi-Level Teaching–Learning-Based Optimization (P-BTLBO) algorithm for hybrid feature extraction and multi-class brain tumor classification using ResNet-50 and... by Mahananda Malkauthekar, Avinash Gulve, Ratnadeep Deshmukh

“…The suggested P-BTLBO method makes the combined set of features better by repeatedly focusing on higher-level and lower-level goals: improving classification accuracy while removing unnecessary features. …”
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Improving forest above-ground biomass estimation using genetic-based feature selection from Sentinel-1 and Sentinel-2 data (case study of the Noor forest area in Iran) by Armin Moghimi, Ava Tavakoli Darestani, Nikrouz Mostofi, Mahdiyeh Fathi, Meisam Amani

“…In this study, we employed a Genetic Algorithm (GA) to estimate forest Above-Ground Biomass (AGB) by selecting the most applicable features from both Sentinel-2 optical and Sentinel-1 Synthetic Aperture Radar (SAR) images in the Noor forest. …”
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