Metaheuristics in automated machine learning: Strategies for optimization by Francesco Zito, El-Ghazali Talbi, Claudia Cavallaro, Vincenzo Cutello, Mario Pavone

“…We examine various metaheuristic algorithms employed and, in particular, their effectiveness in improving model performance across diverse applications. …”
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Multi-Objective Intelligent Routing Algorithm for LEO Satellite Networks Based on DQN by LUO Zongyi, JIN Shichao, DONG Tao, YIN Jie

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Post-integration based point-line feature visual SLAM in low-texture environments by Yanli Liu, Zhengyuan Feng, Heng Zhang, Wang Dong

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An Intelligent Inspection and Scheduling Algorithm for Integrated Pipe Gallery Based on Cloud Robot by ZHOU Xiwei, SHANG Xiao, SHANG Xinjuan, YAN Maode, WANG Fafa

“…In order to solve the problem of multiple iterations and poor real-time performance, it proposed an improved adaptive weight particle swarm optimization-genetic hybrid optimization algorithm combined with particle swarm optimization and genetic algorithm. …”
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Application of Genetic Algorithms to Solve MTSP Problems with Priority (Case Study at the Jakarta Street Lighting Service) by Sugih Sudharma Tjandra, Fran Setiawan, Hanoum Salsabila

“…In its development based on actual events in the real world, some priorities must be visited first in optimizing vehicle routes. Several studies on MTSP and CVRP models have been conducted with exact solutions and algorithms. …”
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Modelo matemático y algoritmo de solución de un flujo con tiempos dependientes de la secuencia // A mathematical model and solution algorithm to a flow shop task with times dependi... by A. Fiol-Zulueta, J. Arzola-Ruíz, A. da Silva-Carvalho

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Enhanced Vector Quantization for Embedded Machine Learning: A Post-Training Approach With Incremental Clustering by Thommas K. S. Flores, Morsinaldo Medeiros, Marianne Silva, Daniel G. Costa, Ivanovitch Silva

“…This study introduces a novel method to optimize Post-Training Quantization (PTQ), a widely used technique for reducing model size, by integrating Vector Quantization (VQ) with incremental clustering. …”
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An Area-Time Efficient Hardware Architecture for ML-KEM Post-Quantum Cryptography Standard by Trong-Hung Nguyen, Tuan-Kiet Dang, Duc-Thuan Dam, Khai-Duy Nguyen, Phuc-Phan Duong, Cong-Kha Pham, Trong-Thuc Hoang

“…To facilitate the integration of the NIST-standardized post-quantum cryptographic (PQC) algorithm, Module Lattice-based Key Encapsulation Mechanism (ML-KEM), into quantum-resistant devices and cryptosystems, this study introduces an area-time efficient hardware implementation. …”
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Local Outlier Detection Method Based on Improved K-means by Yu ZHOU, Hao XIA, Xuezhen YUE, Peichong WANG

“…Hence, an improved K-means clustering algorithm is proposed by introducing fast search and discovering density peak methods. …”
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Combined use of near infrared spectroscopy and chemometrics for the simultaneous detection of multiple illicit additions in wheat flour by Xinyi Dong, Ying Dong, Jinming Liu, Siting Wu

“…Compared to regression models built with competitive adaptive reweighted sampling and genetic algorithm for feature wavelength selection, the performance improved significantly, enhancing generalization capability. …”
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Simulation of automatic intrusion detection in university networks by using neural network algorithms by Houdun Xu

“…Using appropriate training methods and optimization algorithms, train and optimize the neural network model to achieve high accuracy and robustness. …”
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Adaptive Controller Design for Improving Helicopter Flying Qualities by Wei Wu

“…In online system identification module, a recursive extended least squares algorithm is established to identify the augmented linear flight dynamics model which is composed of helicopter model and unideal noise model. …”
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Guided Particle Swarm Optimization for Feature Selection: Application to Cancer Genome Data by Simone A. Ludwig

“…It involves selecting a subset of relevant features for use in model construction. Feature selection helps in improving model performance by reducing overfitting, enhancing generalization, and decreasing computational cost. …”
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Optimization Scheduling of Multiple Heterogeneous Energy Sources by Ying Zhao, Zhiwen Yu, Xiaobin Wang, Jianlin Tang, Xiaoming Lin, Fan Zhang, Bin Qian

“…The study summarizes the mainstream mathematical modeling and optimization algorithms, intelligent optimization techniques, and real-time data processing technologies. …”
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Design of Enhanced License Plate Information Recognition Algorithm Based on Environment Perception by Zilu Wang, Limin Zheng, Gang Li

“…Comparing the H-YOLO detector with the baseline YOLOv11 model, we found that the training precision and recall of our model were improved by 2.62% and 1.8%, respectively. …”
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Application of Particle Swarm Algorithm in Nanoscale Damage Detection and Identification of Steel Structure by Ying Zhang

“…Second, two test functions are used to compare and analyze, which shows that the improved particle swarm algorithm has better optimization performance. …”
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Myocarditis Detection Using Proximal Policy Optimization and Mutual Learning by Asadi Srinivasulu, Sivaram Rajeyyagari

“…To address class imbalance, a proximal policy optimization (PPO)-based algorithm is utilized, significantly improving the training process by preventing abrupt policy shifts and stabilizing them. …”
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Analyzing Post-fire Vegetation Dynamics with Ultra-high Resolution Remote Sensing Data by O. Petrov, O. Petrov, A. Medvedev

“…This study highlights the potential of UAV-based multi-temporal monitoring for post-fire forest assessment. Future research should focus on improving tree segmentation of SfM-MVS point clouds in dense canopies, optimizing co-alignment under varying environmental conditions, and integrating additional point cloud classification methods to improve accuracy in areas with complex species distribution.…”
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Automatic strip layout design in progressive dies using the grouping genetic algorithm by Mehran Afshari, Behrooz Arezoo

“…In the present study, a new method is presented for the automatic strip layout design for progressive dies using the Grouping Genetic Algorithm. A two-objective function is used in the optimization process. …”
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Optimal distributed generation placement and sizing using modified grey wolf optimization and ETAP for power system performance enhancement and protection adaptation by Nasreddine Bouchikhi, Fethi Boussadia, Riyadh Bouddou, Ayodeji Olalekan Salau, Saad Mekhilef, Chaima Gouder, Sarra Adiche, Abdallah Belabbes

“…The MGWO algorithm is an improved version of the conventional GWO algorithm, which is based on a hierarchical model inspired by the social behavior of grey wolves. …”
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