GAPO: A Graph Attention-Based Reinforcement Learning Algorithm for Congestion-Aware Task Offloading in Multi-Hop Vehicular Edge Computing by Hongwei Zhao, Xuyan Li, Chengrui Li, Lu Yao

“…Building on this foundation, an attention-based Actor–Critic framework makes joint offloading decisions by intelligently selecting the optimal destination and collaboratively determining the ratios for offloading and resource allocation. A multi-objective reward function, designed to minimize task latency and to alleviate link congestion, guides the entire learning process. …”
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Fairness-Aware Utility Maximization for Multi-UAV-Aided Terrestrial Networks by Nishant Gupta, Satyam Agarwal, Aymen Fakhreddine

“…However, this integration presents various technical challenges, including coordination, interference management, and dynamic allocation of resources. To address these key challenges, in this paper, we maximize the network utility by jointly optimizing the scheduling and cell association, transmit power of all base stations, and ABS deployment locations in the presence of co-channel interference. …”
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Methods for Cognitive Diagnosis of Students’ Abilities Based on Keystroke Features by Xu Chi, Xinyu Guo, Yu Sheng

“…This provides strong support for the formulation of teaching strategies and the allocation of resources, and the method possesses important application value and practical significance.…”
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Simulation study on the urban-rural integration circulatory mechanism system in China: Based on system dynamics model and multi-objective genetic algorithm by Gaoyang Liang, Mingqiang Xing, Jianqiang Zhao

“…Additionally, multi-objective optimization solutions are proposed using a Multi-Objective Genetic Algorithm (MOP-GA), which suggest that a comprehensive development strategy that balances urban-rural resource allocation achieves the highest level of integration. …”
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Redefining Trauma Triage for Elderly Adults: Development of Age-Specific Guidelines for Improved Patient Outcomes Based on a Machine-Learning Algorithm by Ji Yeon Lim, Yongho Jee, Seong Gyu Choi, Yoon Hee Choi, Sam S. Torbati, Carl T. Berdahl, Sun Hwa Lee

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Secondary Frequency Control of Islanded Microgrid Based on Deep Reinforcement Learning by Li WANG, Yuxiang JIANG, Xiangjun ZENG, Bin ZHAO, Junhao LI

“…The frequency deviation is used as the state input variable, and the design of the state space, action space, reward function, neural network, and hyperparameters in the deep Q-Networks algorithm is carried out. The reward function balances the goals of frequency recovery and power allocation among distributed energy resources , ensuring consistency in action selection among the intelligent agents. …”
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Optimizing Pharmaceutical Inventory and Investment Strategies During Pandemics: A Dynamic Approach Integrating Environmental Emission Rates and Advanced Optimization Algorithms by Vinita Dwivedi, Mamta Keswani, Uttam Kumar Khedlekar, Lalji Kumar

“…Optimal control theory is applied for dynamic investment adjustments, enhancing resource allocations and decision-making. The study addresses a complex replenishment problem involving joint pricing, environmental costs, order costs, preservation technology, and replenishment schedules for non-instantaneous deteriorating items, aiming to maximize retailer's profit. …”
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A TRIZ-based algorithm for business model innovation in manufacturing SMEs: a systematic framework for strategic innovation integrated with the business model canvas by Juan G. Mejia-Duque, Andres Guerrero-Alvarado

“…A single-case study in a Colombian manufacturing SME demonstrated measurable improvements in resource allocation, cost efficiency, quality, customer engagement, and market opportunity identification, strengthening competitiveness and value creation. …”
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Energy management in autonomous hybrid electric vehicles: A review by Abid H., Kissaoui M., Raihani A., Zaggaf M.H.

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A Novel Self-Configurable Algorithm for Uncoordinated Deployment of Home gNodeBs in 5^th Generation Wireless Networks by Madhusmita Panda, Saraju Prasad Padhy, Meetarani Swain

“…This is primarily due to allocation of resources in a timely and reliable manner. …”
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A computation offloading scheme for energy consumption optimization in Internet of vehicles by Wenxuan GAO, Xinjie YANG

“…In Internet of vehicles (IoV), vehicle-oriented applications are generally computation-intensive and latency-sensitive.Introducing idle computing resources from mobile vehicles as a supplement to network computing power can effectively alleviate the load pressure on edge servers.The problem of task allocation for edge computation offloading in the context of IoV environment were researched.By fully leveraging the combined computing resources of roadside units (RSU), user vehicles, and mobile vehicles within the RSU service range, a computation offloading strategy based on the sparrow search algorithm was proposed and referred to as sparrow search based computation offloading scheme (S²COS), aiming to optimize the overall system energy consumption.In addition, this strategy fully taked into account practical network issues such as service time constraints caused by vehicle mobility and the potential occurrence of computation node failures.The simulation results demonstrate that S²COS can meet the latency requirements for computation-intensive and latency-sensitive tasks, while significantly reducing system energy consumption.…”
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Load balancing method of service cluster based on mean-variance by Xiaoan BAO, Xue WEI, Lei CHEN, Guoheng HU, Na ZHANG

“…When a large number of concurrent requests are allocated,the load scheduling mechanism is to achieve the load balancing of nodes in the network by minimizing the response time and maximizing the utilization ratio of nodes.In the load balancing algorithm based on genetic algorithm,the fitness function is designed to have an important influence on the load balancing efficiency.A service cluster load balancing method based on mean-variance was proposed to optimize the fitness function.The investment portfolio selection model mean-variance was used to minimize the response time,which was used to get the weight of each server's resource utilization,so as to obtain the optimal allocation combination.This method improves the accuracy and efficiency of the fitness function.Compared with other models in different service environment,the simulation results show that the load balancing algorithm makes the service cluster get a better balance performance in terms of node utilization and response time.…”
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A two-stage robust optimization for EV user-friendly VPP participation in ancillary service markets by Yu Wang, Xiangrui Tong, Yiheng Xie, Bing Chen, Ning Tong, Xiaomei Wu

“…The VPP ensures reserves to swiftly respond to market uncertainties. A power allocation strategy was implemented based on a consensus algorithm that takes into account the satisfaction level of EV users participating in ancillary services and the battery degradation cost. …”
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Internet of Things Based Application Placement Technique in Fog Environment by N Malathy, M Ruba, S Vinothini

“…Leveraging an Improved Memetic Algorithm (IMA), this strategy enables effective scheduling of parallel IoT workflows across fog and cloud servers, ensuring balanced resource utilization and enhanced scalability. …”
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Asymptotic quadratic price game mechanism for video stream extensible feedback unloading by Qianqian GE

“…A progressive quadratic price game mechanism with scalable feedback offloading of video streams was proposed.Firstly,the congestion of cellular network could be alleviated by effectively uninstalling some video traffic from all video streaming services to Wi-Fi network,thus providing seamless video streaming services.Several physi-cal paths were integrated in an economical and efficient way.The fountain coded symbols of compressed video data were transmitted simultaneously through LTE and Wi-Fi network to flexibly control the viewing through Wi-Fi net-work and reduce the video quality degradation caused by wireless channel errors.Secondly,a progressive secondary price auction mechanism was used to allocate limited LTE resources to multiple user devices to maximize social wel-fare and achieve Nash equilibrium.The scalability and convergence of the system were verified theoretically.Finally,the performance advantages of the proposed algorithm in video streaming transmission quality and energy consump-tion were verified by experimental simulation.…”
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Multi-objective layout optimization of hospital outpatient clinics based on NSGA II by Yanlin Zhao, Jiamei Gu

“…The research findings provide a reference for the rational allocation of hospital outpatient resources and the improvement of service quality. …”
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Block-Based Adaptive Compressed Sensing by Using Edge Information for Real-Time Reconstruction by V. Pavitra, V. B. S. Srilatha Indira Dutt

“…Adaptive Block-Based Compressed Sensing (ABCS) enables optimization of image and video sensing platforms with limited resources, using novel algorithms for efficient reconstruction and real-time operations. …”
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Usability of machine learning algorithms based on electronic health records for the prediction of acute kidney injury and transition to acute kidney disease: A proof of concept stu... by Lorenzo Ruinelli, Pietro Cippà, Chantal Sieber, Clelia Di Serio, Paolo Ferrari, Antonio Bellasi

“…The high NPV also suggests its implementation as a tool to rule out the risk of renal failure, aid in individualizing patient care, and allocate healthcare resources.…”
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Research on Personnel Image Segmentation Based on MobileNetV2 H-Swish CBAM PSPNet in Search and Rescue Scenarios by Di Zhao, Weiwei Zhang, Yuxing Wang

“…In post-disaster search and rescue scenarios, the accurate image segmentation of individuals is essential for efficient resource allocation and effective rescue operations. …”
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Optimizing quantum convolutional neural network architectures for arbitrary data dimension by Changwon Lee, Israel F. Araujo, Dongha Kim, Junghan Lee, Siheon Park, Ju-Young Ryu, Ju-Young Ryu, Daniel K. Park, Daniel K. Park

“…., the number of features) of the input data that can be processed, restricting the applicability of QCNN algorithms to real-world data. To address this issue, we propose a QCNN architecture capable of handling arbitrary input data dimensions while optimizing the allocation of quantum resources such as ancillary qubits and quantum gates. …”
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