An energy saving clustering algorithm based on artificial bee colony in ultra dense network by Pengguang ZHOU, Junwei HUANG, Renchi ZHANG, Hao XU

“…In ultra dense network (UDN),the dense deployment of low power base station (BS) will increase the system's energy consumption and cause the waste of the scarce spectrum resources.Aiming to explore the feasible method of energy saving system and interference coordination,BS sleeping-waking-active mechanism in UDN was proposed,which would reduce the opening time of the sleeping BS.Also an adjusted artificial bee colony algorithm was proposed which used the least colors to dye the BS in topology,then power allocation of active BS in different cluster was optimized.Simulations show that the sleeping-waking-active mechanism can improve the energy efficiency of the system,and the clustering algorithm can promote the spectrum efficiency and throughput.…”
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An innovative genetic algorithm-based master schedule to optimize job shop scheduling problem by Thi Phuong Quyen Nguyen, Thi Hoa Thuong Le

“…In this scenario, production scheduling has arisen as an essential function that contributes to the effective allocation of organizational resources in the production process, while shortening production time and satisfying customer deadlines. …”
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Storage Location Assignment in Emergency Reserve Warehouses: A Multi-Objective Optimization Algorithm by Chen Liang, Tao Cui, Yu Wei, Kun Zhao, Xiongping Yue, Chao Wang

“…The efficiency of emergency response operations is critically dependent on the strategic storage and allocation of emergency supplies. Proper management of these resources reduces economic impacts and ensures prompt availability in crises. …”
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Dynamic Adaptive Environmental Flows (DAE‐Flows) to Reconcile Long‐Term Ecosystem Demands With Hydropower Objectives by Ana Paula Dalcin, Guilherme Fernandes Marques, Amaury Tilmant, Marcelo Olivares

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Distributed dynamic event-triggered time-varying resource management for microgrids via practical predefined-time multiagent methods by Tingting Zhou, Salah Laghrouche, Youcef Ait-Amirat

“…A novel TV resource management model is introduced, explicitly accounting for dynamic constraints and demand variations to ensure real-time resource allocation while effectively handling load fluctuations and renewable energy variability. …”
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Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

“…Moreover, integrating machine learning into risk management enhances decision-making by providing precise, data-driven predictions, allowing for more effective strategies and efficient resource allocation.Future research could incorporate additional data, such as historical records, economic indicators, and internal process information, to further improve prediction accuracy. …”
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A Dynamic Load Balancing Architecture for Fog Computing using Tree Base Resource Arrangement and Flexible Task Prioritization by Bikash Sarma, R. Kumar, Themrichon Tuithung

“…The proposed method is founded on a tree-based dynamic resources arrangement mechanism that refreshes the fog clusters created using Fuzzy C Mean (FCM) to increase the speed of resource allocation. …”
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Multi-Link Fragmentation-Aware Deep Reinforcement Learning RSA Algorithm in Elastic Optical Network by Jing Jiang, Yushu Su, Jingchi Cheng, Tao Shang

“…Deep reinforcement learning has been extensively applied for resource allocation in elastic optical networks. However, many studies focus on link-level state analysis and rarely discuss the influence between links, which may affect the performance of allocation algorithms. …”
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Efficient task scheduling for cloud computing: a comparative survey of state-of-the-art algorithms by Aziza Algarni

“…Multiple independent tasks need to be handled by cloud computing, and static and dynamic scheduling plays a crucial role in allocating tasks to the right resources. This is especially important in heterogeneous environments, where algorithms can improve load balancing and enhance cloud computing's efficiency. …”
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Developing Resilient and Expandable Adaptive Capacity Arbitration Algorithms for Future WCDMA (UMTS) Wireless Systems by M. Sajjad, S. Qaisar, A. Khan, I. Khan, S. Hussein Khan

“… The objective of this research paper is to tackle the emerging challenges associated with resource management in future WCDMA (UMTS) wireless systems by presenting resilient and expandable adaptive capacity arbitration algorithms. …”
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Fuzzy clustering based scheduling algorithm for minimizing the tasks completion time in cloud computing environment by Nawaf R. Alharbe

“…With its focus on fuzzy resource allocation that considers task composition and priority, BDHEFT streamlines the project schedule, ultimately reducing both execution time and costs. …”
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QoS-aware enhanced proportional faire scheduling algorithm for real-time services in LTE networks by Mahnaz Sotoudeh Bahreyni, Vahid Sattari-Naeini

“…This paper proposes a resource scheduling downlink algorithm for LTE networks. …”
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A Stackelberg game based content caching algorithm in energy-harvesting small cell networks by Xueting WANG, Qi ZHU, Han HU

“…To improve the users' satisfaction of download files, a caching based resource allocation algorithm in energy-harvesting small cell networks was proposed, which was established as a Stackelberg game that jointly optimized user accessing and small cells' content updating. …”
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A dual-layer planning method based on improved MOPSO for distribution networks considering source–load temporal uncertainty by Guilian Wu, Guilian Wu, Jia Lin, Jinlin Liao

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Numerical Algorithm for Solving Market Clearing Problem in Power Electronics-Based Power Distribution Systems by Musharrat Sabah, Aaron M. Cramer, Yuan Liao

“…Market-based control is a control approach that can be used to organize resource control problems by establishing an artificial market economy for the allocation of these resources. …”
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Quantum Approximate Optimization Algorithm for the Max-Cut Problem: JavaScript Programming Language Implementation by Dmytro Sapozhnyk

“…The Max-Cut issue, which involves partitioning the vertices of a graph into two subsets such that the number of edges between the subsets is maximized, is a well-known NP-hard difficulty with numerous practical applications, including network design and resource allocation. The implementation of QAOA in JavaScript is a significant step towards integrating quantum computing with modern web technologies, thus broadening access to quantum algorithms among software developers. …”
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Optimizing protein-ligand docking through machine learning: algorithm selection with AutoDock Vina by Ala’ Omar Hasan Zayed

“…Abstract Context Understanding protein-ligand interactions is fundamental to drug design, where optimizing docking parameter selection can potentially enhance computational efficiency and resource allocation in virtual screening. While numerous algorithms exist for protein-ligand docking, achieving an optimal balance between accuracy and computational speed remains challenging. …”
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A Deep Q-Learning Algorithm With Guaranteed Convergence for Distributed and Uncoordinated Operation of Cognitive Radios by Ankita Tondwalkar, Andres Kwasinski

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Numerical Recognition Algorithm for Power Equipment Monitoring Based on Light-Resnet Convolutional Neural Network by Zhiheng KONG, Chong TAN, Peiyao TANG, Chengbo HU, Min ZHENG

“…This approach, leveraging the allocation of computational resources for task distribution, introduces a Light-Resnet-based numerical recognition algorithm, which enhances network training through the optimization of the D-Add loss function, enabling remote reading of electrical equipment monitoring data. …”
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Enhancing Youbike Redistribution System: A Study on Station Recommendation Using a Genetic Algorithm by Yang-Chou Juan, Yi-Chung Chen, Wei-Ting Chen, Chieh Yang, Chia-Tzu Liu, Yi-Ci Hou, Yi-Hsuan Tsai

“…This study proposes a novel approach to optimize YouBike allocation under resource constraints. We first used K-means clustering to group stations with similar rental profiles, reducing the number of models needed. …”
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