Optimizing Container Placement in Data Centers by Deep Reinforcement Learning by Hyeonjeong Kim, Cheolhoon Lee

“…Specifically, we utilize deep reinforcement learning (DRL), which has been widely applied in various fields, to optimize container placement. Our approach outperforms traditional heuristic algorithms and offers the additional advantage of handling fixed-size inputs, enabling flexible operation regardless of the number of containers. …”
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Fair Probabilistic Multi-Armed Bandit With Applications to Network Optimization by Zhiwu Guo, Chicheng Zhang, Ming Li, Marwan Krunz

“…To address the FP-MAB problem, we propose two algorithms: Fair Probabilistic Explore-Then-Commit (FP-ETC) and Fair Probabilistic Optimism In the Face of Uncertainty (FP-OFU). …”
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Optimized window functions for spectral analysis based on digital filters by R.V. Petrosian

“…The article addresses a relevant issue of improving the accuracy of spectral analysis in computerized systems by optimizing window functions used in the Discrete Fourier Transform (DFT). …”
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A Novel Loss Minimization Algorithm for the 3-Port Converter in a Multi-Subgrid Microgrid by Rajarshi Basu, Mahesh Kumar Mishra

“…Among them, the 3-port converter, previously proposed by the authors, optimizes the integration of different microgrid entities while minimizing the switch count. …”
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Distributed quantile regression over sensor networks via the primal–dual hybrid gradient algorithm by Zheng Qin, Zhaoting Liu

“…Theoretical analyses guarantee the convergence of the proposed algorithm under mild assumptions, while experimental results show that the dPDHG algorithm converges significantly faster than subgradient-based schemes.…”
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Energy Efficiency Optimization in Swarm Robotics for Smart Photovoltaic Monitoring by Dimitris Ziouzios, Nikolaos Baras, Minas Dasygenis, Vayos Karayannis, Constantinos Tsanaktsidis

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Optimizing Personalized and Context-Aware Recommendations in Pervasive Computing Environments by A. C. Kaladevi, V. Vinoth Kumar, T. R. Mahesh, Suresh Guluwadi

“…Reinforcement learning algorithms optimize the recommendation policy based on user feedback. …”
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Integrating Mobile Devices and Wearable Technology for Optimal Sleep Conditions by You-Kwang Wang, Chien-Yu Chen

“…This project uses cloud storage technology and cloud software algorithms to enable data sharing and real-time feedback. …”
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Robust personalized pricing under uncertainty of purchase probabilities by Shunnosuke Ikeda, Naoki Nishimura, Noriyoshi Sukegawa, Yuichi Takano

“…Experimental results demonstrate the effectiveness of our robust optimization model and highlight the utility of our Lagrangian decomposition algorithm in terms of both computational efficiency and solution quality.…”
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Resource allocation strategies and task scheduling algorithms for cloud computing: A systematic literature review by Kareem Awad Waleed, Zainol Ariffin Khairul Akram, Nazri Mohd Zakree Ahmad, Yassen Esam Taha

“…It evaluates popular algorithms designed to optimize key metrics such as energy consumption, resource utilization, cost reduction, makespan minimization, and performance satisfaction. …”
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Long-Term Maintenance Scheduling of Smart Distribution System through a PSO-TS Algorithm by Jianxue Wang, Jianming Lu, Zhaohong Bie, Shutang You, Xiaoyu Cao

“…A combined algorithm that consists of particle swarm optimization and tabu search is designed and applied to the optimization problem. …”
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Performance Evaluation of Hybrid Bio-Inspired and Deep Learning Algorithms in Gene Selection and Cancer Classification by Shahad S. Alkamli, Hala M. Alshamlan

“…This study explores the performance of hybrid bio-inspired algorithms and deep learning techniques for gene selection and cancer classification. …”
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Parametric-modeling-based multi-objective thermoelastic optimization of rudder structures by Shi Guanghui, Bao Yuhao, Wu Wenhua, Guo Guiqiang, Lin Ye, Zhang Xiaopeng, Tao Ran

“…These optimization problems are solved using a compromise programming algorithm. …”
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Grey Wolf Optimization- and Particle Swarm Optimization-Based PD/I Controllers and DC/DC Buck Converters Designed for PEM Fuel Cell-Powered Quadrotor by Habibe Gursoy Demir

“…Both optimizers work together in the system and try to minimize tracking errors while also minimizing power consumption by using suitable objective functions. …”
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An energy-saving virtual machine scheduling algorithm for resource management based on cloud computing technology by Liangyu Zhang

“…Therefore, the algorithm proposed in this paper can effectively reduce energy consumption while avoiding frequent migration of virtual machines, and the innovation in genetic algorithm optimization strategy improves the overall efficiency and stability of scheduling.…”
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DECISION TREE WITH HILL CLIMBING ALGORITHM BASED SPECTRUM HOLE DETECTION IN COGNITIVE RADIO NETWORK by N Suganthi, R Meenakshi, A Sairam, M Parvathi

“…The objective of the DTHC method is to improve detection accuracy while minimizing false alarm rates. The approach integrates a Decision Tree (DT) algorithm for rapid initial classification of Primary User (PU) activity, followed by a Hill Climbing (HC) optimization algorithm that fine-tunes the detection based on a fitness function. …”
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A Novel Energy Replenishment Algorithm to Increase the Network Performance of Rechargeable Wireless Sensor Networks by Tariq, Vishwanath Eswarakrishnan, Adil Hussain, Zhu Wei, Muhammad Uzair

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A Genetic Algorithm Approach for Expedited Crossing of Emergency Vehicles in Connected and Autonomous Intersection Traffic by Qiang Lu, Kyoung-Dae Kim

“…This paper proposes an intersection control algorithm which aims to determine an efficient vehicle-passing sequence that allows the emergency vehicle to cross an intersection as soon as possible while the travel times of other vehicles are minimally affected. …”
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Impact of surrogate model accuracy on performance and model management strategy in surrogate-assisted evolutionary algorithms by Yuki Hanawa, Tomohiro Harada, Yukiya Miura

“…Surrogate-assisted evolutionary algorithms (SAEAs) are widely used to solve expensive optimization problems where evaluating candidate solutions is computationally intensive. …”
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A Hybrid Algorithm for PMLSM Force Ripple Suppression Based on Mechanism Model and Data Model by Yunlong Yi, Sheng Ma, Bo Zhang, Wei Feng

“…Experiments show that the hybrid framework effectively compensates the unmodeled disturbance through the data model while maintaining the physical interpretability of the mechanistic model, which provides a new idea for motor performance optimization under complex working conditions.…”
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