Microservice combination optimisation based on improved gray wolf algorithm by Jingjing Hu, Xiaojun Xu, Jin Hao, Xiuqi Yang, Kefan Qiu, Yuanzhang Li

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Improved grey wolf optimization algorithm based service function chain mapping algorithm by Yue ZHANG, Junnan ZHANG, Xiaochun WU, Chen HONG, Jingjing ZHOU

“…With the rise of new Internet applications such as the industrial Internet, the Internet of vehicles, and the metaverse, the network’s requirements for low latency, reliability, security, and certainty are facing severe challenges.In the process of virtual network deployment, when using network function virtualization technology, there were problems such as low service function chain mapping efficiency and high deployment resource overhead.The node activation cost and instantiation cost was jointly considered, an integer linear programming model with the optimization goal of minimizing the average deployment network cost was established, and an improved grey wolf optimization service function chain mapping (IMGWO-SFCM) algorithm was proposed.Three strategies: mapping scheme search based on acyclic KSP algorithm, mapping scheme coding and improvement based on reverse learning and nonlinear convergence were added to the standard grey wolf optimization algorithm to form this algorithm.The global search and local search capabilities were well balanced and the service function chain mapping scheme was quickly determined by IMGWO-SFCM.Compared with the comparison algorithm, IMGWO-SFCM reduces the average deployment network cost by 11.86% while ensuring a higher service function chain request acceptance rate.…”
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Chain hybrid feature selection algorithm based on improved Grey Wolf Optimization algorithm. by Xiaotong Bai, Yuefeng Zheng, Yang Lu, Yongtao Shi

“…In this paper, we propose a new hybrid feature selection algorithm, to be named as Tandem Maximum Kendall Minimum Chi-Square and ReliefF Improved Grey Wolf Optimization algorithm (TMKMCRIGWO). …”
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Hybrid Algorithm of Particle Swarm Optimization and Grey Wolf Optimizer for Improving Convergence Performance by Narinder Singh, S. B. Singh

“…A newly hybrid nature inspired algorithm called HPSOGWO is presented with the combination of Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO). …”
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Coverage Optimization Technology of Power Pipe Gallery Based on Improved Gray Wolf Algorithm by Cheng ZHONG, Di ZHAI, Yang LU, Xiaobo LIU, Xinru WANG, Xiongwen ZHAO

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Intelligent Layout Method of Ship Pipelines Based on an Improved Grey Wolf Optimization Algorithm by Yongjin Lu, Kai Li, Rui Lin, Yunlong Wang, Hairong Han

“…The improved algorithm has better global search ability, higher solution stability, and faster convergence speed than the standard grey wolf optimization algorithm. …”
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Research on Optimization of Improved Gray Wolf Optimization-Extreme Learning Machine Algorithm in Vehicle Route Planning by Shijin Li, Fucai Wang

“…Extreme Learning Machine (ELM) algorithm model is introduced to accelerate Improved Gray Wolf Optimization (IGWO) optimization and improve convergence speed. …”
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Improved gray wolf harris hawk algorithm based feature selection for sentiment analysis by Tamara Amjad Al-Qablan, Mohd Halim Mohd Noor, Mohammed Azmi Al-Betar, Ahamad Tajudin Khader

“…Efficient sentiment feature selection (FS) is crucial for reducing data dimensionality and isolating relevant features to improve results. This study aims to enhance FS performance by addressing the population diversity issues in the Adaptive β Binary Gray Wolf Optimization (Aβ-BGWO) algorithm, which struggles to escape local optima. …”
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Research on DV-Hop location algorithm based on range correction and improved gray wolf optimizer by Xiaoqiang ZHAO, Shuai WU, Chuanyi GAO, Ning LI, Bodong LI, Xiaoyong YANG

“…Node location is an important problem in wireless sensor network.Although the location algorithm based on distance measurement has small positioning error, it has many limitations when applied to outdoor environments.Therefore, based on the original distance vector-hop (DV-Hop) algorithm, received signal strength indication (RSSI) technology and the minimum mean square error (MMSE) criterion to modify the algorithm’s ranging process were introduced, and the improved gray wolf optimizer was used to optimize the process of determining the coordinates of unknown nodes.Simulation results show that, compared with the original DV-Hop algorithm and IPDV-Hop algorithm, the average location error rate of the IGDV-Hop algorithm under the initial parameters was reduced by 28% and 17% respectively, and the location effect was significantly improved.…”
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Point cloud registration based on surface feature extraction and an improved Grey Wolf Optimization algorithm by Zimei Tu, Yichen Xie, Jinhua Jiang, Qin Qin

“…The extracted feature points serve as the initial values for the improved gray wolf optimization algorithm, which is employed to refine the registration results. …”
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Improved Binary Grey Wolf Optimization Approaches for Feature Selection Optimization by Jomana Yousef Khaseeb, Arabi Keshk, Anas Youssef

“…Three improved binary Grey Wolf Optimization (GWO) approaches are proposed in this paper to optimize the feature selection process by enhancing the feature selection accuracy while selecting the least possible number of features. …”
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Hierarchical multi step Gray Wolf optimization algorithm for energy systems optimization by Idriss Dagal, AL-Wesabi Ibrahim, Ambe Harrison, Wulfran Fendzi Mbasso, Ahmad O. Hourani, Ievgen Zaitsev

“…Abstract Gray Wolf Optimization (GWO), inspired by the social hierarchy and cooperative hunting behavior of gray wolves, is a widely used metaheuristic algorithm for solving complex optimization problems in various domains, including engineering design, image processing, and machine learning. …”
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Hybrid Deep Neural Network Optimization with Particle Swarm and Grey Wolf Algorithms for Sunburst Attack Detection by Mohammad Almseidin, Amjad Gawanmeh, Maen Alzubi, Jamil Al-Sawwa, Ashraf S. Mashaleh, Mouhammd Alkasassbeh

“…Bio-inspired optimization algorithms, especially Particle Swarm Intelligence (PSO) and the Gray Wolf Optimizer (GWO), have been widely used to optimize complex tasks because of their ability to explore the search space and their fast convergence. …”
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Improved Grey Wolf Algorithm: A Method for UAV Path Planning by Xingyu Zhou, Guoqing Shi, Jiandong Zhang

“…The Grey Wolf Optimizer (GWO) algorithm is recognized for its simplicity and ease of implementation, and has become a preferred method for solving global optimization problems due to its adaptability and search capabilities. …”
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Image Segmentation Based on the Optimized K-Means Algorithm with the Improved Hybrid Grey Wolf Optimization: Application in Ore Particle Size Detection by Xinyi Chai, Zijun Wu, Wei Li, Haowei Fan, Xinyang Sun, Jing Xu

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An Improved Multi-Objective Grey Wolf Optimizer for Aerodynamic Optimization of Axial Cooling Fans by Yanzhao Gong, Richard Amankwa Adjei, Guocheng Tao, Yitao Zeng, Chengwei Fan

“…This paper introduces an improved multi-objective grey wolf optimizer (IMOGWO) and demonstrates its application to the aerodynamic optimization of an axial cooling fan. …”
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Grey Wolf Algorithm in Coordinated Hydro and Wind Power Generation by Xing LI, Xiuyuan YANG, Lijie WANG

“…To achieve the coordinated operation of wind power and hydropower and improve the stationarity of the coordinate output, the Grey Wolf algorithm was used to optimize the PID control of hydraulic turbine, to facilitate hydropower steadily track the change of wind power and make the output of wind power and hydropower output according to plan. …”
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Improved grey wolf optimizer for optimal reactive power dispatch with integration of wind and solar energy by F. Laouafi

“…The aim of this paper is to present a new improved grey wolf optimizer (IGWO) to solve the optimal reactive power dispatch (ORPD) problem with and without penetration of renewable energy resources (RERs). …”
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Prioritized Multi‐Step Decision‐Making Gray Wolf Optimization Algorithm for Engineering Applications by Idriss Dagal, Alpaslan Demirci, Ambe Harrison, Wulfran Fendzi Mbasso, Said Mirza Tercan, Burak Akın, Kürşat Tanriöven, Havva Aysun Sezgin Köksal, Ahmet Nayir

“…ABSTRACT This article introduces the Prey‐Movement Strategy Gray Wolf Optimizer (PMS‐GWO), an enhanced version of the Gray Wolf Optimizer (GWO) designed to improve optimization efficiency through a novel multi‐step decision‐making process. …”
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Load Frequency Control Based on Gray Wolf Optimizer Algorithm for Modern Power Systems by Dao Huy Tuan, Dao Trong Tran, Van Nguyen Ngoc Thanh, Van Van Huynh

“…This paper proposes a novel approach to the LFC of the MPS by integrating a proportional–integral–derivative (PID) controller optimized using the gray wolf optimizer (GWO) algorithm. …”
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