An Improved Coral Reef Optimization-Based Scheduling Algorithm for Cloud Computing by Shuzhen Wan, Lixin Qi

“…In this paper, we establish a resource allocation framework and propose a novel task scheduling algorithm. An improved coral reef optimization (ICRO) is proposed to deal with this task scheduling problem. …”
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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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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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Salp Navigation and Competitive based Parrot Optimizer (SNCPO) for efficient extreme learning machine training and global numerical optimization by Oluwatayomi Rereloluwa Adegboye, Afi Kekeli Feda, Ghanshyam G. Tejani, Aseel Smerat, Pankaj Kumar, Ephraim Bonah Agyekum

“…To address these challenges, this paper introduces the Salp Navigation and Competitive based Parrot Optimizer (SNCPO), a novel hybrid algorithm that integrates Competitive Swarm Optimization (CSO) and the Salp Swarm Algorithm (SSA) into the PO framework. …”
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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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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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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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YOLO-WWBi: An Optimized YOLO11 Algorithm for PCB Defect Detection by Yi Zhao, Zhidi Jiang

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Optimizing DVA placement using evolutionary algorithms for dynamic beam loading by Podwórna Monika, Grosel Jacek

“…Moreover, the optimization of DVAs leads to the asymmetry of the absorber’s position along the length of a bridge’s beam. …”
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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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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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Optimization of Deep Neural Networks Using a Micro Genetic Algorithm by Ricardo Landa, David Tovias-Alanis, Gregorio Toscano

“…This work proposes the use of a micro genetic algorithm to optimize the architecture of fully connected layers in convolutional neural networks, with the aim of reducing model complexity without sacrificing performance. …”
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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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Quantum approximate optimization algorithms for maximum cut on low-girth graphs by Tongyang Li, Yuexin Su, Ziyi Yang, Shengyu Zhang

“…In quantum computing, Farhi, Gutmann, and Goldstone proposed the quantum approximate optimization algorithm (QAOA) for solving the MaxCut problem. …”
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An Optimized Power Load Forecasting Algorithm Based on VMD‐SMA‐LSTM by Wei Liu, Fan Hua, Yongping Cui, Yangchao Xu, Han Liu

“…This study introduces an enhanced power load forecasting algorithm, integrating slime mould algorithm (SMA) and long short‐time memory (LSTM) to effectively address the hyperparameter challenges associated with LSTM, while also applying variational modal decomposition (VMD) to load forecasting. …”
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Optimal Speed and Position Controller for PMDC Motor Based GWO Algorithm by Iman S. Kareem, Sahar R. Al-Sakini, Ghassan A. Bilal

“…The Grey Wolf Optimizations GWO Algorithm, is the newer technique to optimize the uncertain optimization problems by autotuning parameters. …”
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