Research on Multi-Center Path Optimization for Emergency Events Based on an Improved Particle Swarm Optimization Algorithm by Zeyu Zou, Hui Zeng, Xiaodong Zheng, Junming Chen

“…Experimental findings underscore the potential of the proposed approach in optimizing emergency response logistics. The hybrid algorithm consistently achieves significant reductions in total cost while maintaining fairness in material distribution. …”
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Optimal Design of Multiband Microstrip Antennas by Self-Renewing Fitness Estimation of Particle Swarm Optimization Algorithm by Xiaohong Fan, Yubo Tian, Yi Zhao

“…In order to reduce the time of designing microstrip antenna, this paper proposes a self-renewing fitness estimation of particle swarm optimization algorithm (SFEPSO) to improve the design efficiency. …”
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Optimization of New Energy Vehicle Industry Structure Based on Optimization Link Prediction Similarity Algorithm and CGE by Zhenjun Xie

“…In light of the growing global concerns over energy and climate change, new energy vehicles are confronted with both opportunities and challenges posed by industrial structural transformation. To foster the optimization of the new energy vehicle industry structure while considering environmental impact, this paper first uses an improved link prediction algorithm to construct an industrial structure optimization model. …”
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“Optimizing the Optimization”: A Hybrid Evolutionary-Based AI Scheme for Optimal Performance by Agathoklis A. Krimpenis, Loukas Athanasakos

“…This collaborative process seeks to achieve optimal solutions at reduced convergence costs. This mixed scheme was tested on challenging benchmark functions, demonstrating convergence speeds that were at least three times faster than the best-performing standalone algorithms while maintaining solution quality. …”
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GP4ESP: a hybrid genetic algorithm and particle swarm optimization algorithm for edge server placement by Fang Han, Hui Fu, Bo Wang, Yaoli Xu, Bin Lv

“…Due to NP-hardness of ESP, some works have designed meta-heuristic algorithms for solving it. While these algorithms either exploited only one kind of meta-heuristic search strategies or separately perform two different meta-heuristic algorithms. …”
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Exploring the Orca Predation Algorithm for Economic Dispatch Optimization in Power Systems by Vivi Aida Fitria, Arif Nur Afandi, Aripriharta

“…This research shows that Orca Predation Algorithm consistently does better than other bio-inspired algorithms like Particle Swarm Optimization, Whale Optimization Algorithm, Grey Wolf Optimizer, the Bat Algorithm, Genetic Algorithm and Ant Colony Optimization in terms of minimum cost, average cost, and solution stability. …”
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Balancing the Parameters of Perforated Solar Screens to Optimize Daylight and Glare Performance in Office Buildings by Aya M.F. El-Bahrawy

“…Genetic algorithms and the Python component in Grasshopper were utilized to identify the optimal balanced solutions. …”
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An Improved Coral Reef Optimization-Based Scheduling Algorithm for Cloud Computing by Shuzhen Wan, Lixin Qi

“…Experimental results show that compared with other algorithms, ICRO can significantly reduce the makespan and cost of the scheduling, while maintaining a better load balance in the system.…”
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Application of Blocplan and Aldep Algorithms for Optimizing Production Layout at Meatball Factory by Thabed Tholib Baladraf

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Modification of the genetic algorithm for comprehensive topological optimization of the synchronous motors rotor by T. I. Petrov

“…The aim is to develop a methodology for topological complex optimization of the engine design, based on a genetic algorithm.METHODS. …”
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Multiple strategy enhanced hybrid algorithm BAGWO combining beetle antennae search and grey wolf optimizer for global optimization by Fan Zhang, Chuankai Liu, Peng Liu, Shuiting Ding, Tian Qiu, Jiajun Wang, Huipeng Du

“…Abstract This study proposes BAGWO, a novel hybrid optimization algorithm that integrates the Beetle Antennae Search algorithm (BAS) and the Grey Wolf Optimizer (GWO) to leverage their complementary strengths while enhancing their original strategies. …”
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EG-DPoS: Optimized DPoS Consensus Algorithm Based on Evolutionary Game by LIU Yong, DENG Xiaohong, LIU Lihui, SHI Yiran, ZHANG Li

“…Aiming at the problems of low enthusiasm among voting nodes, bribery from malicious nodes, and the vulnerability of sequential block generation by agent nodes in the delegated proof of stake (DPoS) consensus process, an optimized DPoS consensus algorithm based on evolutionary game theory (EG-DPoS) is proposed. …”
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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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Research on performance optimizations for TCM-KNN network anomaly detection algorithm by LI Yang1, GUO Li1, LU Tian-bo3, TIAN Zhi-hong1

“…Based on TCM-KNN（transductive confidence machine for K-nearest neighbors） algorithm,the filter-based feature selection and cluster-based instance selection methods were used towards optimizing it as a lightweight network anomaly detection scheme,which not only reduced its complex feature space,but also acquired high quality instances for training.A series of experimental results demonstrate the two methods for optimizations are actually effective in greatly reducing the computational costs while ensuring high detection performances for TCM-KNN algorithm.Therefore,the two methods make TCM-KNN be a good scheme for a lightweight network anomaly detection in practice.…”
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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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Path Optimization of Welding Robot Based on Ant Colony and Genetic Algorithm by Yan Gao, Yiwan Zhang

“…At the same time, the robot with optimized genetic algorithm has smaller fluctuations in joint angle and angular velocity in the simulated welding task, and the optimization algorithm takes 17.6 s less than the traditional particle swarm algorithm and 11 s less than the single A∗ algorithm. …”
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Exploring Evolutionary Algorithms for Multi-Objective Optimization in Seismic Structural Design by Seda Göktepe Körpeoğlu, Süleyman Mesut Yılmaz

“…While genetic algorithms are used to improve both the cost and seismic performance of the structure, particle swarm optimization is used to optimize the vibration and displacement performance of structures. …”
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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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Intelligent anti-jamming decision algorithm based on proximal policy optimization by MA Song, LI Li, LI Wei, HUANG Wei, WANG Jun

“…Aiming at the above problems, an intelligent anti-jamming decision algorithm based on proximal policy optimization was proposed, which deployed the decision-making neural network and the training neural network in the vehicles and the ground station, respectively. …”
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