IGWO-MSVR model for predicting stress in coal seam during drilling process by Jian Tan, Yanfeng Geng, Liangke Xu

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Various optimization algorithms for efficient placement and sizing of photovoltaic distributed generations in different networks. by Ahmed A Zaki Diab, Fayza S Mahmoud, Hamdy M Sultan, Abou-Hashema M El-Sayed, Mohamed A Ismeil, Omar Makram Kamel

“…Various optimization techniques, namely Salp Swarm Algorithm (SSA), Marine Predictor Algorithm (MPA), Grey Wolf Optimizer (GWO), Improved Grey Wolf Optimizer (IGWO), and Seagull Optimization Algorithm (SOA), have been applied to achieve optimal allocation and sizing of RDGs in radial distributed systems (RDS). …”
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Energy optimization using adaptive control algorithm to enhance the performance of SDN_IOT environment by I. Varalakshmi, M. Thenmozhi

“…The system reduces energy consumption by 18%, improves detection accuracy by 2% (from 97.5% to 99.4%), and lowers the false positive rate to 0.01% compared to existing algorithms. …”
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An Enhanced Genetic Algorithm for Optimized Educational Assessment Test Generation Through Population Variation by Doru-Anastasiu Popescu

“…The most important aspect of a genetic algorithm (GA) lies in the optimal solution found. …”
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Urban flood hazard assessment using FLA-optimized boost algorithms in Ankara, Türkiye by Enes Gul

“…By applying advanced boosting algorithms—specifically, XGBoost, GradientBoost, and CatBoost—along with hyperparameter optimization through the Fick’s law algorithm (FLA), this research introduces an innovative methodology aimed at improving the reliability and accuracy of flood hazard assessments in Ankara’s urban landscape. …”
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A FPGA Accelerator of Distributed A3C Algorithm with Optimal Resource Deployment by Fen Ge, Guohui Zhang, Ziyu Li, Fang Zhou

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A Fast Satellite Selection Algorithm Based on Hierarchical Clustering and Iterative Subset Optimization by Dan Jing, Weidie Li, Liang Han, Xinchen Li, Liangchao Li, Yan Zhang, Liang Guo, Mengdao Xing

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Flow direction algorithm for optimal coordination of directional overcurrent relays considering arc flash by Dina K. Mahmoud, Shady H．E．Abdel Aleem, Ahmed M. Ibrahim, Mahmoud M. Sayed, Wael Abdelfattah

“…This paper presents a novel meta-heuristic optimization method called flow direction algorithm (FDA) to achieve optimal coordination of Directional Overcurrent Relays (DOCRs) while considering the impact of Arc Flash (AF). …”
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Optimization Design Method of Pipe-Insulating Joints Based on Surrogate Model and Genetic Algorithm by Chen Guo, Zheng Yang, Jianbo Dong, Yanchao Yue, Linjun Tian, Ping Ma

“…This improves the computational efficiency of the optimization algorithm by establishing a surrogate model, which can be used to optimize the dimensions of insulation joints.…”
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Joint Optimization Algorithm for UAV-Assisted Caching and Charging Based on Wireless Energy Harvesting by Yumeng Zhu, Qi Zhu

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A novel solid waste instance creation for an optimized capacitated vehicle routing model using discrete smell agent optimization algorithm by Ahmed T. Salawudeen, Olusesi A. Meadows, Basira Yahaya, Muhammed B. Mu'azu

“…The developed model was optimized using a new discrete smell agent optimization (SAO) algorithm and compared to firefly algorithm (FA) and particle swarm optimization (PSO). …”
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Image cluster algorithm of hybrid encoding method by Chun-hui ZHAO, Xue-yuan LI, Ying CUI

“…In the clustering analysis based on swarm intelligence optimization algorithm,the most of encoding method only used single form,and this method might be limit range of search space,the algorithm was easy to fall into local op-timum.In order to solve this problem,image clustering algorithm of hybrid encoding (HEICA) was proposed.Firstly,a hybrid encoding model based on image clustering was established,this method could expand the scope of the search space.Meanwhile,it was combined with two optimization algorithms which improved rain forest algorithm (IRFA) and quantum particle swarm optimization (QPSO),this method could improve the global search capability.In the simulation experiment,it was carried out to illustrate the performance of the proposed method based on four datasets.Compared with results form four measured cluster algorithm.The experimental results show that the algorithm has strong global search capability,high stability and clustering effect.…”
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Post-Anesthesia Care Unit (PACU) readiness predictions using machine learning: a comparative study of algorithms by Shahnam Sedigh Maroufi, Maryam Soleimani Movahed, Azar Ejmalian, Maryam Sarkhosh, Ali Behmanesh

“…Abstract Introduction Accurate and timely discharge from the Post-Anesthesia Care Unit (PACU) is essential to prevent postoperative complications and optimize hospital resource utilization. …”
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Dynamic Optimization of Xylitol Production Using Legendre-Based Control Parameterization by Eugenia Gutiérrez, Marianela Noriega, Cecilia Fernández, Nadia Pantano, Leandro Rodriguez, Gustavo Scaglia

“…This paper presents an improved methodology for optimizing the fed-batch fermentation process of xylitol production, aiming to maximize the final concentration in a bioreactor co-fed with xylose and glucose. …”
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An Improved MOEA/D Based on Reference Distance for Software Project Portfolio Optimization by Jing Xiao, Jing-Jing Li, Xi-Xi Hong, Min-Mei Huang, Xiao-Min Hu, Yong Tang, Chang-Qin Huang

“…In this paper, we propose an improved MOEA/D (multiobjective evolutionary algorithm based on decomposition) based on reference distance (MOEA/D_RD) to solve the software project portfolio optimization problems with optimizing 2, 3, and 4 objectives. …”
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Exponential Improvements in the Simulation of Lattice Gauge Theories Using Near-Optimal Techniques by Mason L. Rhodes, Michael Kreshchuk, Shivesh Pathak

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An Improved Large Neighborhood Search for Network-Level Airport Slot Allocation Optimization by Qiangzhe Wang, Yuanyuan Ma, Yifan Xu, Zhiyuan Shen, Dan Li

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Optimizing RetinaNet anchors using differential evolution for improved object detection by Asaad Mohammed, Hosny M. Ibrahim, Nagwa M. Omar

“…Specifically, we propose an optimization algorithm based on Differential Evolution (DE) that adjusts anchor scales and ratios while determining the most appropriate number of these parameters for each dataset based on the annotated data. …”
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Large-scale post-disaster user distributed coverage optimization based on multi-agent reinforcement learning by Wenjun XU, Silei WU, Fengyu WANG, Lan LIN, Guojun LI, Zhi ZHANG

“…In order to quickly restore emergency communication services for large-scale post-disaster users, a distributed intellicise coverage optimization architecture based on multi-agent reinforcement learning (RL) was proposed, which could address the significant differences and dynamics of communication services caused by a large number of access users, and the difficulty of expansion caused by centralized algorithms.Specifically, a distributed k-sums clustering algorithm considering service differences of users was designed in the network characterization layer, which could make each unmanned aerial vehicle base station (UAV-BS) adjust the local networking natively and simply, and obtain states of cluster center for multi-agent RL.In the trajectory control layer, multi-agent soft actor critic (MASAC) with distributed-training-distributed-execution structure was designed for UAV-BS to control trajectory as intelligent nodes.Furthermore, ensemble learning and curriculum learning were integrated to improve the stability and convergence speed of training process.The simulation results show that the proposed distributed k-sums algorithm is superior to the k-means in terms of average load efficiency and clustering balance, and MASAC based trajectory control algorithm can effectively reduce communication interruptions and improve the spectrum efficiency, which outperforms the existing RL algorithms.…”
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Large-scale post-disaster user distributed coverage optimization based on multi-agent reinforcement learning by Wenjun XU, Silei WU, Fengyu WANG, Lan LIN, Guojun LI, Zhi ZHANG

“…In order to quickly restore emergency communication services for large-scale post-disaster users, a distributed intellicise coverage optimization architecture based on multi-agent reinforcement learning (RL) was proposed, which could address the significant differences and dynamics of communication services caused by a large number of access users, and the difficulty of expansion caused by centralized algorithms.Specifically, a distributed k-sums clustering algorithm considering service differences of users was designed in the network characterization layer, which could make each unmanned aerial vehicle base station (UAV-BS) adjust the local networking natively and simply, and obtain states of cluster center for multi-agent RL.In the trajectory control layer, multi-agent soft actor critic (MASAC) with distributed-training-distributed-execution structure was designed for UAV-BS to control trajectory as intelligent nodes.Furthermore, ensemble learning and curriculum learning were integrated to improve the stability and convergence speed of training process.The simulation results show that the proposed distributed k-sums algorithm is superior to the k-means in terms of average load efficiency and clustering balance, and MASAC based trajectory control algorithm can effectively reduce communication interruptions and improve the spectrum efficiency, which outperforms the existing RL algorithms.…”
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