GNN-based optimization algorithm for joint user scheduling and beamforming by Shiwen HE, Jun YUAN, Zhenyu AN, Min ZHANG, Yongming HUANG, Yaoxue ZHANG

“…The coordinated multi-point (CoMP) transmission technology has the characteristics of reducing co-channel interference and improving spectral efficiency.For the CoMP technology, user scheduling (US) and beamforming (BF) design are two fundamental research problems located in the media access control layer and the physical layer, respectively.Under the consideration of user service quality requirements, the joint user US-BF optimization problem was investigated with the goal of maximizing network throughput.To overcome the problem that the traditional optimization algorithm had high computational cost and couldn’t effectively utilize the network historical data information, a joint US and power allocation (M-JEEPON) model based on graph neural network was proposed to realize joint US-BF optimization by combining the beam vector analytical solution.The simulation results show that the proposed algorithm can achieve the performance matching or even better than traditional optimization algorithms with lower computational overhead.…”
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Long short‐term memory‐based forecasting of uncertain parameters in an islanded hybrid microgrid and its energy management using improved grey wolf optimization algorithm by Raji Krishna, Hemamalini S

“…Results demonstrate that the improved grey wolf optimization (IGWO) algorithm is more effective at reducing costs and provides faster optimal solutions.…”
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Edge server deployment decision based on improved NSGA-Ⅱ in the Internet of vehicles edge computing scenario by Sifeng ZHU, Yu WANG, Hao CHEN, Hai ZHU, Zhengyi CHAI, Chengrui YANG

“…In the context of the Internet of vehicles, the placement and deployment number of edge servers directly affect the efficiency of edge computing.Due to the high cost of deploying a large edge server on a macro base station and a base station, it can be complemented by deploying a small edge server on a micro base station, and the cost reduction needs to be optimized by optimizing the placement of large edge servers.In order to minimize the deployment cost and service delay of the edge server, and maximize the operator’s revenue and server load balance, the edge server placement problem combined with the vehicle networking user application service was modeled as a multi-objective optimization problem and a placement scheme based on improved NSGA-Ⅱ algorithm was proposed.The experimental results show that the proposed scheme can reduce the deployment cost of edge servers by about 44%, the latency by about 14.2%, and improve the revenue of operators by 24.2%, which has good application value.…”
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Applying Genetic Algorithm for test pattern generation process optimization by V. I. Kuraedov

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Optimization of Wheel Reprofiling Based on the Improved NSGA-II by Xinghu Wang, Jiabin Yuan, Sha Hua, Bojia Duan

“…As a method to maintain the shape at the cost of the diameter size, reprofiling has significant impacts on the lifecycle of a train. …”
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DEVELOPMENT OF THE ALGORITHM FOR CHOOSING THE OPTIMAL SCENARIO FOR THE DEVELOPMENT OF THE REGION'S ECONOMY by I. S. Borisova

“…It was found that the rationale and choice of the optimal scenario is an important stage in the development of the sustainable development program of the regional economy, since it helps to quantify the most probable trajectories of changes in the activities of all participants in the region's economy.Conclusions and Relevance: the practical significance of the developed algorithm lies in the possibility of using it to improve the stability of the development of the economy of specific regions. …”
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Increasing integration of wind energy through the joint operation of electric vehicles and the grid using the intelligent spider monkey algorithm by Han Xiaoming, Qian Jingjing

“…A significant innovation involves demonstrating that prohibitive constraints on simultaneous charging and discharging can, under specific conditions, be relaxed without compromising system stability, thereby simplifying the optimization process. The optimization problem is formulated as a single objective problem and solved using an improved spider monkey optimization algorithm. …”
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Ensemble machine learning algorithm for cost-effective and timely detection of diabetes in Maiduguri, Borno State by Emmanuel Gbenga Dada, Aishatu Ibrahim Birma, Abdulkarim Abbas Gora

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A binary grasshopper optimization algorithm for solving uncapacitated facility location problem by Ahmet Babalik, Aybuke Babadag

“…The Uncapacitated Facility Location Problem (UFLP) is a real-world binary optimization problem that aims to find the number of facilities to open, minimizing the total cost of exchange between customers and facilities, as well as the opening costs of these facilities. …”
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Optimization of distribution networks using quantum annealing for loss reduction and voltage improvement in electrical vehicle parking management by Naser Rashnu, Babak Mozafari, Reza Sharifi

“…Traditional optimization techniques like Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) often struggle with the nonlinear, high-dimensional nature of EV-grid interaction problems. …”
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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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Operation Optimization Strategy of Commercial Combined Electric Heating System Based on Particle Swarm Optimization Algorithm by WANG Qing, LI Congcong, WANG Pingxin, WU Qingqing, CAI Xiaoyu

“… In order to improve the energy efficiency of the electric heating system, a particle swarm optimization (PSO, Particle Swarm Optimization)-based operation optimization strategy for the direct storage combined electric heating system is proposed.A mathematical model of influencing factors inside and outside the walls of electric heating buildings is established, and the simulink toolbox in matlab is used to build the overall system under the premise of determining the quantity of electric heating.Combining demand response ideas, the objective function is to establish the minimum heating and electricity cost of the user, and different sub-modules are selected to form the control module to achieve simulation verification, and the inverse cosine method is used to update the improved particle swarm algorithm to update the learning factor to solve the set objective function.Finally, through a calculation example of electricity consumption data of an enterprise in Jinan, Shandong, comparing energy consumption and economy can be obtained: the total energy consumption throughout the day is lower than the actual energy consumption, and the electricity bill is reduced by 17.16% compared with the unoptimized time.…”
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Adaptive Multi-Objective Firefly Optimization for Energy-Efficient and QoS-Aware Scheduling in Distributed Green Data Centers by Ahmed Chiheb Ammari, Wael Labidi, Rami Al-Hmouz

“…To solve this, we propose an Adaptive Firefly-Based Bi-Objective Optimization (AFBO) algorithm that introduces multiple adaptive mechanisms to improve convergence and diversity. …”
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Ship’s Trajectory Planning Based on Improved Multiobjective Algorithm for Collision Avoidance by Jinxin Li, Hongbo Wang, Wei Zhao, Yuanyuan Xue

“…In this paper, the optimization of ship collision avoidance strategies is realized by both an improved multiobjective optimization algorithm NSGA-II and the ship domain under the condition of a wide sea area without any external disturbances. …”
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Design of improved JAYA algorithm for cigarette finished product logistics delivery by Jun Wen, Yewei Hu, Le Li, Zongrui Wu, Guangwei Xiao, Kai Guo, Lei Li

“…In response to these challenges, this study proposes an improved Jaya algorithm that integrates a reverse learning mechanism and a cosine similarity strategy to enhance optimization performance. …”
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Path Planning of Quadrupedal Robot Based on Improved RRT-Connect Algorithm by Xiaohua Xu, Peibo Li, Jiangwu Zhou, Wenzhuo Deng

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An Improved Hybrid Genetic Algorithm with a New Local Search Procedure by Wen Wan, Jeffrey B. Birch

“…One important challenge of a hybrid genetic algorithm (HGA) (also called memetic algorithm) is the tradeoff between global and local searching (LS) as it is the case that the cost of an LS can be rather high. …”
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AC Optimal Power Flow Problem Considering Wind Energy by an Improved Particle Swarm Optimization by Mohammad Reza Ansari, Hossein Ramzaninezhad

“…To solve the AC-OPF model, an Improved Particle Swarm Optimization (IPSO) is presented. …”
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Insulator Defect Detection Algorithm Based on Improved YOLOv11n by Junmei Zhao, Shangxiao Miao, Rui Kang, Longkun Cao, Liping Zhang, Yifeng Ren

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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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