Spatial Position Optimization of Components in the Labeling Robot System for Bundled Bars by Zhang Fuxiang, Zheng Yu, Huang Yongjian, Wang Chunmei, Huang Fengshan

“…Taking the shortest total stroke of the robot labeling process as the optimization goal of the placement position of the industrial robot and label printer, an improved particle swarm optimization algorithm is used for optimization calculation to obtain the optimal spatial position of the industrial robot and label printer, which improves the work efficiency of the labeling robot system, and has guiding significance for the practical application of the system.…”
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Democratization of Crop Irrigation: A Socio-Technical Optimization Approach Using Particle Swarm Optimization by Hasna Elalaoui Elabdallaoui, Youssef Mourdi, Abdelaziz ElFazziki, Mohamed Sadgal

“…It examines how this equitable irrigation approach can contribute to the social economy by improving irrigation efficiency and reducing costs for farmers. …”
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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

“…An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …”
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An Energy Management Optimization Strategy for Regional Power Grid Energy Storage System Based on Improved Artificial Bee Colony Algorithm by Ziqi WANG, Huiyuan ZHANG, Jun XU, Jiehui CHENG

“…Simulation results show that the energy management optimization of energy storage can improve the overall economic benefits, and the improved artificial bee colony algorithm has good global search ability and convergence.…”
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An Improved Hybrid Ant Colony Optimization and Genetic Algorithm for Multi-Map Path Planning of Rescuing Robots in Mine Disaster Scenario by Jingrui Zhang, Zhenhong Xu, Houde Liu, Xiaojun Zhu, Bin Lan

“…An improved hybrid algorithm combining ant colony optimization (ACO) and genetic algorithm (GA) is then proposed to solve the established model. …”
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An Energy-Efficient Thrust Allocation Based on the Improved Dung Beetle Optimizer for the Dynamic Positioning System of Vessels by Yulong Tuo, Jianlong Lin, Zhouhua Peng, Yuanhui Wang, Shasha Wang

“…The proposed HOATDBO algorithm has perfect global and local optimization capabilities, which can quickly and reliably obtain the optimal thrust solution, improve the thrust allocation accuracy of vessels, and reduce energy consumption. …”
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Determining the optimal generalization operators for building footprints using an improved graph neural network model by Xinyu Niu, Haizhong Qian, Xiao Wang, Limin Xie, Longfei Cui

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Analysis of optimal configuration of energy storage in wind-solar micro-grid based on improved gray wolf optimization by Huang Qian, Huang Dengke, Cai Li, Xu Qingshan

“…The mathematical model of the improved gray wolf optimization is constructed, and the typical landscape resource data of a residential district. …”
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Bone scintigraphy based on deep learning model and modified growth optimizer by Omnia Magdy, Mohamed Abd Elaziz, Abdelghani Dahou, Ahmed A. Ewees, Ahmed Elgarayhi, Mohammed Sallah

“…In addition, the second phase is named feature selection, and it is dependent on the Arithmetic Optimization Algorithm (AOA) being used to improve the Growth Optimizer (GO). …”
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Vertebra CT Image Segmentation Method Based on Improved U-Net Model by LIU Xia, YU Hong-bo, LI Bing, WANG Bo

“…Firstly，it was improved and optimized on the basis of the classic u-net model. …”
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Revolutionizing RPAS logistics and reducing CO2 emissions with advanced RPAS technology for delivery systems by Armin Mahmoodi, Leila Hashemi, Jeremy Laliberte, Richard C. Millar, Robert Walter Meyer

“…The use of the NSGA-II meta-heuristic method for validation enhances the credibility and practicality of the model. The optimization model’s performance over 250 generations shows rapid initial improvements in cost, time, risk, and battery usage, followed by stabilization, indicating efficient convergence and effective evolutionary computation. …”
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Developing a Machine Learning-Driven Model that Leverages Meta-Heuristic Algorithms to Forecast the Load-Bearing Capacity of Piles by Tianhua Zhou

“…Additionally, it uses two separate meta-heuristic optimization methods, namely the Golden Jackal optimization algorithm (GJO) and Smell Agent Optimization (SAO), to achieve the best possible results. …”
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Enhanced CO₂ Emissions Prediction Using Temporal Fusion Transformer Optimized by Football Optimization Algorithm by Amel Ali Alhussan, Marwa Metwally

“…Feature selection using the Football Optimization Algorithm (FbOA) significantly improved its performance, reducing the RMSE to 0.018798774. …”
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Stochastic Multi-objective Distribution Network Reconfiguration Considering Wind Turbines by Ehsan Azad Farsani, Mohsen Zare

“…The objectives of proposed DNR policy are minimization of active power losses, total electrical energy costs, and total emissions of the network. To solve the problem, an improved version of Honey Bee Mating Optimization (IHBMO) algorithm is implemented. …”
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Parameter optimization of ship anti-roll gyro control system based on genetic algorithm by Tongtong QIE, Jianyong ZHENG, Lei ZHANG, Zhichu LEI, Xutao HE

“…ObjectiveIn order to improve the performance of the anti-roll gyro, a passive control parameter optimization method based on a genetic algorithm is proposed. …”
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TOPSIS inspired cost-efficient concurrent workflow scheduling algorithm in cloud by K. Kalyan Chakravarthi, L. Shyamala, V. Vaidehi

“…Therefore, it is a great challenge to improve system performance and optimize several scheduling criteria simultaneously. …”
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Ship path planning based on improved multi-scale A* algorithm of collision risk function by Chunyu Song, Teer Guo, Jianghua Sui

“…Moreover, in order to improve the efficiency of optimal path planning in the context of complex sea areas while ensuring path safety, the paper proposes a collision risk function to optimize the determination of the cost of A* algorithm nodes, thereby enhancing the heuristic function of the A* algorithm. …”
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Development of an optimization model for a monitoring point in tunnel stress deduction using a machine learning algorithm by Xuyan Tan, Weizhong Chen, Luyu Wang, Wei Ye

“…Therefore, with the aim of optimizing the monitoring scheme, this study introduces a spatial deduction model for the stress distribution of the overall structure using a machine learning algorithm. …”
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Rejection-Free Monte Carlo Simulation of QUBO and Lechner–Hauke–Zoller Optimization Problems by Yoshihiro Nambu

“…Landscapes of success probabilities of finding the globally optimal solution as well as feasible solutions were evaluated as a function of a set of hyper-parameters used to characterize the weights of cost and penalty functions. …”
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Tuning Genetic Algorithm Parameters to Improve Convergence Time by Maria Angelova, Tania Pencheva

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