Programmable composite pipeline structure supporting scheduling of integrated network and computing by HOU Saifeng, CUI Pengshuai, HU Yuxiang, DONG Yongji, LIU Yi

“…The heterogeneous resource allocation strategy was solved based on resource pricing and cooperative game to realize the flexible scheduling of computing and network resources in the process of data forwarding. …”
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Asset management using an extended Markowitz theorem by Paria Karimi

“…The method has been widely used to solve many applications, successfully. In this paper, we present a multi objective Markowitz model to determine asset allocation by considering cardinality constraints. …”
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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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Presenting a multi-objective decision-making model for cost-time trade-off considering the time value of money and solving it using particle swarm optimization by Mohammadreza Shahriari

“…This model assists project managers in gaining better insight into cost-time impacts, optimizing resource allocation, and ultimately improving project performance by reducing delays.…”
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ADVCSO: Adaptive Dynamically Enhanced Variant of Chicken Swarm Optimization for Combinatorial Optimization Problems by Kunwei Wu, Liangshun Wang, Mingming Liu

“…For collaborative multi-subproblem optimization, the ADVCSO exhibits a superior performance in both Multiple Traveling Salesman Problems (MTSPs) and Multiple Knapsack Problems (MKPs), reducing the maximum path length in MTSPs by 6.0% to 358.27 units while enhancing the MKP optimal solution success rate by 62.5%. The proposed algorithm demonstrates an exceptional performance in combinatorial optimization and holds a significant engineering application value.…”
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Optimization model of electricity metering management based on MOPSO by Sheng Li, Xiaodan Zhou

“…Abstract In response to the difficulty of balancing economy and accuracy in traditional energy metering management methods, an improved particle swarm optimization model is designed to optimize energy metering management based on multi-objective particle swarm optimization, thereby achieving optimal resource allocation and maximizing management efficiency. …”
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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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A Mobile Wireless Sensor Coverage Optimization Method for Bridge Monitoring by Cong Mu, Jiguang Yang, Jiuyuan Huo

“…Aiming at the problem of resource allocation optimization of heterogeneous mobile wireless sensor (HMWS) networks in bridge structural health monitoring, this study proposes an enhanced coverage strategy for heterogeneous sensors based on an improved Hiking Optimization Algorithm (HOA). …”
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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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Quantum-Inspired Hyperheuristic Framework for Solving Dynamic Multi-Objective Combinatorial Problems in Disaster Logistics by Kassem Danach, Hassan Harb, Louai Saker, Ali Raad

“…Disaster logistics presents a highly complex decision-making challenge under conditions of uncertainty, where the timely and efficient allocation of scarce resources is essential to minimize human suffering. …”
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Exploring the Role of Artificial Intelligence in Wastewater Treatment: A Dynamic Analysis of Emerging Research Trends by Javier De la Hoz-M, Edwan Anderson Ariza-Echeverri, Diego Vergara

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Research on elite hierarchical task offloading strategy based on reinforcement learning in edge-cloud collaboration scenario by Juan FANG, Zhiyuan YE, Mengyuan ZHANG, Jiamei SHI, Ziyi TENG

“…With the development of 5G and the enrichment of application functions, applications have put forward higher requirements on the computing capabilities of terminal devices.In order to improve the computing capabilities of terminal devices on applications and reduce the processing time of tasks, it is aimed at mobile edge computing environments, a task offloading method for edge-cloud collaboration was proposed，and an elite hierarchical evolutionary algorithm combined with reinforcement learning (RL-EHEA) was designed to perform offloading decisions, so that multiple tasks with dependencies and deadlines compete for computing resources.The simulation experiment results show that, compared with genetic algorithm (GA) and elite genetic algorithm (EGA), RL-EHEA can shorten task processing time and obtain better resource allocation strategy.…”
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Reinforcement Learning Solutions for Microgrid Control and Management: A Survey by Pedro I. N. Barbalho, Anderson L. Moraes, Vinicius A. Lacerda, Pedro H. A. Barra, Ricardo A. S. Fernandes, Denis V. Coury

“…It is an alternative to traditional algorithms and control methods in tasks, such as load frequency control, resource allocation, and energy management. …”
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A spherical fuzzy WASPAS approach to prioritize the factors enhancing the effectiveness of physical education classroom teaching by Yuhan Gao, Ali Yu

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Mitigating Dead Node Impact on Coverage and Connectivity in Wireless Sensor Networks Using a Hybrid Approach by Omeed K. Khorsheed

“…Previous research in the same context indicates the need for further investigation to achieve optimal trade-offs in network resource allocation. This research introduces a hybrid Artificial Bee Colony-Sequential Re-connectivity and Coverage Algorithm (ABC-SRCA) approach, combining the ABC algorithm with a developed SRCA. …”
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Interpretable Machine Learning for Multi-Energy Supply Station Revenue Forecasting: A SHAP-Driven Framework to Accelerate Urban Carbon Neutrality by Zhihui Zhao, Minjuan Wang, Jin Wei, Xiao Cen, Shengnan Du, Ziwen Wu, Huanying Liu, Weiqiang Wang

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Power Adaptation for Optimizing Secrecy Energy Efficiency in NOMA-Enabled Underlay Cognitive Radio Networks and DNN-Based Evaluation by P. P. Hema, A. V. Babu

“…The computation of the JOTPA for the SUs is enabled by an iterative algorithm that utilizes the Dinkelbach method. It is demonstrated that the suggested JOTPA scheme significantly enhances the SEE of the secondary network in comparison to the random transmit power allocation and equal transmit power allocation strategies. …”
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Pilot-Based Codebook Non-Orthogonal Artificial Noise Schemes for Physical Layer Security: Secrecy Capacity Optimization Under Unknown Eavesdropper Channels by Yi Zhang, Yebo Gu, Tao Zhao, Bo Wang

“…Considering the eavesdropper as an illegitimate user, whose channel state information matrix is unknown to the legitimate receiver and does not follow a simple distribution pattern, this study employs random matrix theory to model the channel of an unknown eavesdropper. It uses the successive convex approximation algorithm to analyze the optimal power allocation strategy and the maximum number of eavesdropper antennas that the system can tolerate under these conditions. …”
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