Optimization of Dye and Plasticizer Concentrations in Halochromic Sensor Films for Rapid pH Response Using Bird-Inspired Metaheuristic Algorithms by Daeuk Kim, Ronnie S. Concepcion, Joseph Rey H. Sta. Agueda, Jubert C. Marquez

“…Optimization of BTB (0.01–0.05%) and PEG (6–10%) concentrations was conducted using bird-inspired metaheuristic algorithms, including the Parrot Optimizer (PO), Pelican Optimization Algorithm (POA), and Secretary Bird Optimization Algorithm (SBOA). …”
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Optimization and Dynamic Adjustment of Tandem Columns for Separating an Ethylbenzene–Styrene Mixture Using a Multi-Objective Particle Swarm Algorithm by Guangsheng Jiang, Yibo She, Zhongwen Song, Liwen Zhao, Guilian Liu

“…A steady-state model is developed to minimize total energy consumption (TEC) and total annualized cost (TAC) by optimizing the reflux flow rates. An integrated dynamic model is created using the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm. …”
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Optimal machine learning algorithms and UAV multispectral imagery for crop phenotypic trait estimation: a comprehensive review and meta-analysis by Adama Ndour, Gerald Blasch, João Valente, Bisrat Haile Gebrekidan, Tesfaye Shiferaw Sida

“…Since previous studies described the broad applications of UAVs and sensors in agriculture, this review aimed to provide a targeted, systematic and quantitative analysis of optimal use of machine learning algorithms and UAV-based multispectral imagery for plant phenotyping.…”
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Optimization on construction machinery considering sequence-dependent setup times and personnel fatigue based on the improved gray wolf and whale algorithm. by Dawei Wang, Bo Gao, Lei Zhang

“…A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. …”
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Comparative Study of Genetic Algorithms and Particle Swarm Optimization for Flexible Power Point Tracking in Photovoltaic Systems under Partial Shading by Ouatman Hamid, Boutammachte Nour-Eddine

“…This study conducts a comparative analysis of Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) for Flexible Power Point Tracking (FPPT) in photovoltaic (PV) systems. …”
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Optimization of power output in plateau photovoltaic power stations using a hybrid Kepler and Gaussian quantum particle swarm algorithm by Shuang Gan, Heng Hu, Shaoshuai Li, Qian Peng, Taidong Yan, Huasheng Gong, Yuancheng Zhang

“…The proposed solution integrates the Kepler Optimization Algorithm (KOA) with the Gaussian Quantum Improved Particle Swarm Optimization (GQPSO) to address multi-objective optimization, with the goal of maximizing power generation, minimizing operational costs, and enhancing system stability. …”
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A diffusion equation based algorithm for determination of the optimal number of fibers used for breast cancer treatment planning in photodynamic therapy by F. S. Ismael, H. M. Amasha, W. H. Bachir

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Edge–Region Collaborative Segmentation of Potato Leaf Disease Images Using Beluga Whale Optimization Algorithm with Danger Sensing Mechanism by Jin-Ling Bei, Ji-Quan Wang

“…DSBWO demonstrates superior optimization performance on the CEC2017 benchmark, with faster convergence and higher accuracy than other algorithms. …”
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MRP-YOLO: An Improved YOLOv8 Algorithm for Steel Surface Defects by Shuxian Zhu, Yajie Zhou

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Genetic Algorithm for Optimizing Urban District and Block Morphology to Minimize Solar Radiation Access and Maximize Building Floor Area in the UAE by Hanan M. Taleb, Mays Kayed, Fuad Baba

“…Further SRA analysis is conducted at the urban block level, focusing on blocks with the highest SRA in the optimized UD to achieve further SRA reduction while maintaining the same FA. …”
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A Hybrid Nondominant-Based Genetic Algorithm (NSGA-II) for Multiobjective Optimization to Minimize Vibration Amplitude in the End Milling Process by Mahesh Gopal, Endalkachew Mosisa Gutema, Hirpa G. Lemu, Jaleta Sori

“…To find the best feasible response, the nondominant sorting genetic algorithm II (NSGA II) approach was trained and tested using MATLAB software. …”
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A New Method for Spectral Wavelength Selection Based on Multiple Linear Regression Combined with Ant Colony Optimization and Genetic Algorithm by Qing Huang, Heru Xue, Jiangping Liu, Xinhua Jiang

“…In this paper, we propose a wavelength selection algorithm based on the ant colony optimization (ACO), in which the absolute value of the regression coefficient of the multiple linear regression (MLR) model is used as the basis for evaluating the importance of wavelengths, and the absolute value of the regression coefficient after full wavelength MLR modeling is used as the initial pheromone value of the ant colony optimization (MLR-ACO). …”
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Optimal Distributed Dispatch of Smart Multi-Agent Energy Hubs Based on Consensus Algorithm Considering Lossy Communication Network and Uncertainty by Abdelfattah A. Eladl, Magda I. El-Afifi, Magdi M. El-Saadawi, Bishoy E. Sedhom

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Sustainable economic production quantity optimization (SEPQ) considering food waste emission and water waste emission using genetic algorithm by Windy Puspika, Ilyas Masudin, Thomy Eko Saputro, Salman Alfarisi, Dian Palupi Restuputri, S. Sarifah Radiah Shariff

“…This study presents a novel approach for optimizing Sustainable Economic Production Quantity (SEPQ) by incorporating food waste and water waste emissions into the production planning process through the use of a Genetic Algorithm (GA). …”
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Optimizing Autonomous Multi-UAV Path Planning for Inspection Missions: A Comparative Study of Genetic and Stochastic Hill Climbing Algorithms by Faten Aljalaud, Yousef Alohali

“…GA exemplifies the global search strategy, while HC illustrates an enhanced stochastic local search. …”
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Predicting CO₂ Emissions with Advanced Deep Learning Models and a Hybrid Greylag Goose Optimization Algorithm by Amel Ali Alhussan, Marwa Metwally, S. K. Towfek

“…In this paper, we propose a general framework that combines advanced deep learning models (such as GRU, Bidirectional GRU (BIGRU), Stacked GRU, and Attention-based BIGRU) with a novel hybridized optimization algorithm, GGBERO, which is a combination of Greylag Goose Optimization (GGO) and Al-Biruni Earth Radius (BER). …”
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Optimal Sizing of a Hybrid Renewable Energy System for Auxiliary Services in Substations Through Genetic Algorithm and Variable Neighborhood Search by Matheus Holzbach, John Fredy Franco Baquero, Mariana Resener

“…The results demonstrate that the proposed sizing approach successfully minimizes costs while ensuring reliability, highlighting its potential to optimize hybrid renewable backup systems for critical substation loads.…”
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Mexican axolotl optimization algorithm with a recalling enhanced recurrent neural network for modular multilevel inverter fed photovoltaic system by R. Madavan, B. Karthikeyan, R. Palanisamy, Mohammad Imtiyaz Gulbarga, Mohammed Al Awadh, Liew Tze Hui

“…Unlike traditional multilevel inverters (MLI), the MMI structure utilized in this work requires fewer power electronic components, reducing cost and complexity. The MAO algorithm optimally tunes control gain parameters offline, creating a dataset of optimal control signals, while the RERNN method predicts and applies real-time control signals, ensuring an efficient and stable power supply. …”
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Developing an Optimized Energy-Efficient Sustainable Building Design Model in an Arid and Semi-Arid Region: A Genetic Algorithm Approach by Ahmad Walid Ayoobi, Mehmet Inceoğlu

“…A comprehensive analysis and optimization model was developed using genetic algorithms to individually optimize various sustainable strategies. …”
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Finite Element Model Updating for a Continuous Beam-Arch Composite Bridge Based on the RSM and a Nutcracker Optimization Algorithm by Weihua Zhou, Hongyin Yang, Jing Hao, Mengxiang Zhai, Hongyou Cao, Zhangjun Liu, Kang Wang

“…The results indicate that the proposed method reduced the average frequency error from 5.58% to 2.75% by updating the model parameters. While the whale optimization algorithm required 21 iterations and the grey wolf optimizer needed 41 iterations to converge near the minimum, the NOA achieved this in merely 13 iterations, demonstrating the NOA’s superior convergence speed. …”
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