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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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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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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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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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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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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Development and validation of a probability-assessment nomogram for non-suicidal self-injury in hospitalized adolescents and young adults with mental disorders by Qi Liu, Yanjuan Ren, Yalin Huang, Ruyi Xie, Yinyuan Li, Zaiquan Dong, Xiaoxia Zhang

“…This detective model can support the rational allocation of medical resources and facilitate the early detection and intervention of NSSI behaviors in hospitalized adolescents and young adults.…”
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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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An analytical framework for regional integration development in the Guangdong-Hong Kong-Macao Greater Bay Area urban agglomeration using fuzzy clustering by Manchang Du

“…Collaboration and resource allocation will be maximized through the CUD-FCA, creating a more integrated and cost-effective urban agglomeration. …”
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Half-hourly electricity price prediction model with explainable-decomposition hybrid deep learning approach by Sujan Ghimire, Ravinesh C. Deo, Konstantin Hopf, Hangyue Liu, David Casillas-Pérez, Andreas Helwig, Salvin S. Prasad, Jorge Pérez-Aracil, Prabal Datta Barua, Sancho Salcedo-Sanz

“…Accurate prediction of electricity price (EP) is crucial for energy utilities and grid operators for enhancing the energy trading, grid stability studies, resource allocations and pricing strategies, thereby improving the overall grid reliability, efficiency, and cost-effectiveness. …”
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Quantum-enhanced digital twin IoT for efficient healthcare task offloading by Ahmed K. Jameil, Hamed Al-Raweshidy

“…However, existing Digital Twin (DT)-based healthcare models suffer from high latency, inefficient resource allocation, cybersecurity vulnerabilities, and computational limitations when processing large-scale patient data. …”
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Traffic Classification in Software-Defined Networking Using Genetic Programming Tools by Spiridoula V. Margariti, Ioannis G. Tsoulos, Evangelia Kiousi, Eleftherios Stergiou

“…The classification of Software-Defined Networking (SDN) traffic is an essential tool for network management, network monitoring, traffic engineering, dynamic resource allocation planning, and applying Quality of Service (QoS) policies. …”
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DQN Simulation Model of Green Cooperative Market Behavior of Multi-Load Users for Optimal Evolution of New-Type Power System by ZHANG Shuo, YUAN Chunhui, LI Yingzi, XIAO Yangming, WEI Ming, HE Yunzheng

“…[Objective] To investigate and analyze the driving role of the green behavior of multiple loads on the evolution of a new type of power system and to enhance the flexibility and resource optimization allocation capacity of a new type of power system， this study conducted a simulation study of the green cooperative market behavior of multiple loads and constructed a simulation model of the green cooperative market behavior of multiple loads under the optimization of the evolution of a new power system. …”
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A Novel Performance Evaluation Framework for Sponge City Construction by Le Luo, Lei Yang, Wang Jiang

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A hybrid deep learning-based intrusion detection system for EV and UAV charging stations by Rosebell Paul, Mercy Paul Selvan

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Dynamic scheduling strategies for cloud-based load balancing in parallel and distributed systems by Nasser S. Albalawi

“…The allocation step is followed by the Hybrid Ant Genetic Algorithm (HAGA), which is used to schedule tasks in parallel. …”
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Decision-Making Model for Life Cycle Management of Aircraft Components by Igor Kabashkin, Vitaly Susanin

“…The study contributes a scalable approach to predictive maintenance, balancing safety, cost, and resource allocation in dynamic operational environments.…”
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Application of expert systems in civil engineering by Ena Grčić, Marija Šperac

“…Artificial neural networks are effective in optimizing financial plans, estimating the duration of activities, assessing the productivity of work teams, and selecting contractors. Genetic algorithms find their application in resource allocation, selecting optimal solutions for task scheduling and project costs, as well as in building maintenance, while fuzzy logic aids in risk analysis, project management, and cost estimation. …”
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A GIS-based integrative approach for land use optimization in a semi-arid watershed by S.M. Tajbakhsh, H. Memarian, A. Kheyrkhah

“…In this study, five categories of land uses, i.e. irrigated orchard, rangeland, irrigated farming, rainfed farming and almond orchard were spatially optimized to minimize surface runoff and sediment yield and to increase net income by integrating three approaches: weighted goal programming, analytic hierarchy process and multi-objective land allocation algorithm. To achieve the target levels in this work, the acreages of almond orchard and rainfed farming should be reduced by 100% and 37.32% respectively, and irrigated farming acreage should be increased by 138.53%. …”
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