Research on Algorithms for Local Robot Positioning Using Methods of Discrete Optimization by Vyacheslav Korolyov, Maksim Ogurtsov, Oleksandr Khodzinskyi

“…For constructing the relative coordinate system, a method of forming a base triangle using a nonlinear discrete optimization method was proposed. An algorithm for building a local positioning system for a robot group was developed to ensure the stable configuration of the group in the absence of access to global or cellular navigation systems while performing tasks in two-dimensional spaces. …”
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A Group Search Algorithm for Optimal Scheduling of Cascade Hydropower Stations by WANG Kechao, CAI Ruoyi, SHEN Jianjian

“…The coronavirus herd immunity optimizer (CHIO) algorithm was introduced to address the optimal scheduling problem of cascade hydropower plants, and an improved algorithm called LCHIO was proposed. …”
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Resource optimization algorithm of combination of NFV and SDN for application of multiple services by Xiaorong ZHU, Qian ZHANG

“…Various services of internet of things (IoT) require flexible network deployment to guarantee different quality of service (QoS).Aiming at the problem of IoT service function chain deployment,network function virtualization (NFV) and software defined networking (SDN) were combined to optimize resources.Considering forwarding cost and traffic load balance,a joint optimization model of virtual network function placement and service function chain routing was given and was proved to be NP-Hard.In order to solve this model,two heuristic algorithms were proposed.One was the service chain deployment algorithm of first routing then placing (FRTP) and the other was the placing followed by routing (PFBR) based on node priority.Simulation results demonstrate that FRTP and PFBR algorithm can significantly balance network traffic load while alleviating congestion and improving the acceptance ratio of the chain requests compared with other algorithms.…”
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A Group Search Algorithm for Optimal Scheduling of Cascade Hydropower Stations by WANG Kechao, CAI Ruoyi, SHEN Jianjian

“…The coronavirus herd immunity optimizer (CHIO) algorithm was introduced to address the optimal scheduling problem of cascade hydropower plants, and an improved algorithm called LCHIO was proposed. …”
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YOLO-WWBi: An Optimized YOLO11 Algorithm for PCB Defect Detection by Yi Zhao, Zhidi Jiang

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Distributed K-Means algorithm based on a Spark optimization sample. by Yongan Feng, Jiapeng Zou, Wanjun Liu, Fu Lv

“…To address the instability and performance issues of the classical K-Means algorithm when dealing with massive datasets, we propose SOSK-Means, an improved K-Means algorithm based on Spark optimization. …”
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CSA: Utility Optimization Scheduling Algorithm for IoT Blockchain Sharding Committees by Xin Cong, Qi Jing, Lingling Zi, Changjiang Lin

“…CSA dynamically adjusts the committee members to achieve near-optimal solutions while addressing operational constraints. …”
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A Hybrid Optimization Algorithm for the Synthesis of Sparse Array Pattern Diagrams by Youzhi Liu, Linshu Huang, Xu Xie, Huijuan Ye

“…The algorithm enhances global search capability through the introduction of a quantum potential well model, while incorporating adaptive mutation operations to prevent premature convergence, thereby improving optimization accuracy during later iterations. …”
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Hybrid strategy enhanced crayfish optimization algorithm for breast cancer prediction by Yu-Jiong Li

“…When combined with Extreme Learning Machine (ELM) and applied to the Wisconsin breast cancer dataset, the MSCOA-ELM model achieved 100% accuracy and F1 score, a 28.9% improvement over the baseline ELM, demonstrating the algorithm’s efficiency and generalization ability in solving practical optimization problems.…”
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Length Optimization of MEP Pipeline Integrated Modular Based on Genetic Algorithm by Xuefeng Zhao, Qiantai Yang, Gangwen Yan, Xiongtao Fan, Yinghui Yang, Huizhong Zhang, Song Chen

“…This paper discusses the advantages and limitations of the proposed method and suggests future directions for further optimizing the algorithm and improving module partitioning. …”
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Optimized Negative Selection Algorithm for Image Classification in Multimodal Biometric System by Monsurat Omolara Balogun, Latifat Adeola Odeniyi, Elijah Olusola Omidiora, Stephen Olatunde Olabiyisi, Adeleye Samuel Falohun

“…Hence, this work developed an Optimized Negative Selection Algorithm (ONSA) for image classification in biometric systems. …”
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Optimization of the Offshore Wind Turbines Layout Using Cuckoo Search Algorithm by Ibrahim Abdulwahab, Solomon Andrew Onazi, Gideon Rimamfate, Akande Abdulwasiu, Abubakar Umar, N.A Iliyasu

“…After-which a cuckoo search algorithm technique is employed in the wind farm model to optimize the optimization problem (minimizing the wake effect while improving power output and cost). …”
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Optimized conductor selection and phase balancing in unbalanced distribution networks: Economic optimization via the vortex search algorithm by Brandon Cortés-Caicedo, Jhony Andrés Guzmán-Henao, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña, Rubén Iván Bolaños

“…This methodology is compared against the hurricane optimization algorithm, the sine cosine algorithm, and the salp swarm optimization algorithm. …”
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Optimizing energy constrained target localization and tracking with radial bias and seeker optimization algorithms in wireless sensor networks by S. Yazhinian, S. Famila, P. Jose, Mahendar A, Sofia R

“…It is seen that the proposed RadB_SOA achieves 12.4 % of transmission error, 14.6 % of ranging error, 96.3 % of localization coverage, 98.65 % of PDR, and 21.56 % of energy consumption. • The Radial Bias-Seeker Optimization Algorithm (RadB_SOA) suggested enhances the precision in target localization and optimizes energy usage in wireless sensor networks. • Simulation outcomes reveal improved tracking accuracy, minimized transmission and ranging errors, as well as increased localization coverage over current techniques. • The research presents an extensive evaluation of particle count fluctuations in RBSO, demonstrating enhanced positioning speed and precision with network efficiency.…”
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Research on Two-Stage Energy Storage Optimization Configurations of Rural Distributed Photovoltaic Clusters Considering the Local Consumption of New Energy by Yang Liu, Dawei Liu, Keyi Kang, Guanqing Wang, Yanzhao Rong, Weijun Wang, Siyu Liu

“…Taking a Chinese village as an example, the proposed model is optimized with an improved particle swarm optimization algorithm. …”
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MAOA: A Swift and Effective Optimization Algorithm for Linear Antenna Array Design by Anoop Raghuvanshi, Abhinav Sharma, Abhishek Kumar Awasthi, Abhishek Sharma, Rahul Singhal, Kim Soon Chong, Sew Sun Tiang, Wei Hong Lim

“…This paper presents the modified arithmetic optimization algorithm (MAOA), a swift and effective optimization algorithm specifically designed for electromagnetic applications. …”
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Distributed Optimization Strategy for Voltage Regulation in PV-Integrated Power Systems with Limited Sensor Deployment by Xun Lu, Junlei Liu, Xinmiao Liu, Jun Liu, Lingxue Lin

“…The methodology integrates an adaptive step size algorithm within a dynamic projected primal–dual distributed optimization framework, eliminating manual parameter tuning requirements while ensuring theoretical convergence guarantees through Lyapunov stability analysis. …”
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A hybrid renewable energy system for Hassi Messaoud region of Algeria: Modeling and optimal sizing by Yacine Bourek, El Mouatez Billah Messini, Chouaib Ammari, Mohamed Guenoune, Boulerbah Chabira, Bipul Krishna Saha

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Improving Forest Above-Ground Biomass Estimation Accuracy Using Multi-Source Remote Sensing and Optimized Least Absolute Shrinkage and Selection Operator Variable Selection Method by Er Wang, Tianbao Huang, Zhi Liu, Lei Bao, Binbing Guo, Zhibo Yu, Zihang Feng, Hongbin Luo, Guanglong Ou

“…The Lasso-GA method results in an ETR model with an R² of 0.73 and an RMSE of 16.70 Mg/ha. Compared to the optimal SGBoost model with the Lasso variable selection method (R² of 0.69, RMSE of 18.63 Mg/ha), the VIF-Lasso method improves R² by 0.06 and reduces RMSE by 2.15 Mg/ha, while the Lasso-GA method improves R² by 0.04 and reduces RMSE by 1.93 Mg/ha. …”
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Do Sharpness-Based Optimizers Improve Generalization in Medical Image Analysis? by Mohamed Hassan, Aleksandar Vakanski, Boyu Zhang, Min Xian

“…These sharpness-based optimizers have shown improvements in model generalization compared to conventional stochastic gradient descent optimizers and their variants on general domain image datasets, but they have not been thoroughly evaluated on medical images. …”
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