Enhancing Surgery Scheduling in Health Care Settings With Metaheuristic Optimization Models: Algorithm Validation Study by João Lopes, Tiago Guimarães, Júlio Duarte, Manuel Santos

“…MethodsCHUdSA’s surgical scheduling process was analyzed over a specific period. By testing an optimization approach, the research team was able to prove the potential of artificial intelligence (AI)–based heuristic models in minimizing scheduling penalties—the financial costs incurred by procedures that were not scheduled on time. …”
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A Novel Network Optimization Scheme Based on Anti-Flocking and Improved Nash Equilibrium Algorithm by Tianjun Wang, Shuchang Zhang, Lishan Liu, Duanpo Wu, Xinyu Jin, Shuwei Cen, Bing Fan

“…Simulation results show that the average service rate of User Equipment (UE) with U-GWO algorithm is improved from 1 % to 5.77 % compared to other different swarm intelligence optimization algorithms. …”
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Proposing a flood management solution based on optimal usage allocation via genetic algorithm by Davood Mokhtari, Aliakbar Rasouli, Monire Moosabeigi

“…In this regard, GIS capabilities could be applied as one of the novel scientific and technical methods along with taking the advantage of Artifcial intelligence capabilities, such as multi-objective genetic algorithm. …”
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A Hybrid Optimization Algorithm for a Multi-Objective Aircraft Loading Problem With Complex Constraints by Boliang Zhang, Yu Yao, H. Y. Kan, Mei-Pou Chan, Chan-Tong Lam, Sio-Kei Im

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Multiphase Transport Network Optimization: Mathematical Framework Integrating Resilience Quantification and Dynamic Algorithm Coupling by Linghao Ren, Xinyue Li, Renjie Song, Yuning Wang, Meiyun Gui, Bo Tang

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Enhancing 5G Vehicular Edge Computing Efficiency with the Hungarian Algorithm for Optimal Task Offloading by Mohamed Kamel Benbraika, Okba Kraa, Yassine Himeur, Khaled Telli, Shadi Atalla, Wathiq Mansoor

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Optimizing Vital Signs in Patients With Traumatic Brain Injury: Reinforcement Learning Algorithm Development and Validation by Hongwei Zhang, Mengyuan Diao, Sheng Zhang, Peifeng Ni, Weidong Zhang, Chenxi Wu, Ying Zhu, Wei Hu

“…In external validation, the AI strategy still has a high survival rate of 87.565%, with an expected return of 27.517. ConclusionsThis RL algorithm for patients with TBI indicates that a more personalized and targeted optimization of the vital signs is possible. …”
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Minimization of Material Waste Through Maintenance Interval Optimization in Transport Systems by Augustyn Lorenc, Małgorzata Kuźnar

“…Although the case study is based on railway vehicles, the approach is applicable to road, maritime, and air transport as well. By leveraging optimization algorithms, such as machine learning, this solution predicts optimal maintenance timing, thereby reducing resource consumption and improving operational efficiency. …”
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A genetic algorithm approach to green vehicle routing: Optimizing vehicle allocation and route planning for perishable products by Hayati Mukti Asih, Raden Achmad Chairdino Leuveano, Dhimas Arief Dharmawan, Ardiansyah Ardiansyah

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Applications of Metaheuristic Algorithms in Solar Air Heater Optimization: A Review of Recent Trends and Future Prospects by Jean De Dieu Niyonteze, Fumin Zou, Godwin Norense Osarumwense Asemota, Walter Nsengiyumva, Noel Hagumimana, Longyun Huang, Aphrodis Nduwamungu, Samuel Bimenyimana

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Optimization and Multimachine Learning Algorithms to Predict Nanometal Surface Area Transfer Parameters for Gold and Silver Nanoparticles by Steven M. E. Demers, Christopher Sobecki, Larry Deschaine

“…With that motivation, two artificial intelligence/machine learning (AI/ML) algorithms, multilayer perception and least absolute shrinkage and selection operator regression, gave a correlation coefficient, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula>, greater than <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0.97</mn></mrow></semantics></math></inline-formula>, indicating that the small dataset was not overfitting and was method-independent. …”
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Improving Search Accuracy in Large-Scale Biased Multiobjective Optimization Through Local Search by Feng Yin, Bin Cao

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Application of Optimal Scheduling Model Based on Improved Genetic Algorithm in Electric Power Mobile Operation by Rui Fan, Huiying Jing, Zhixin Jing

“…In order to solve the current situation, an optimized scheduling model for power mobile jobs based on improved genetic algorithm is proposed. …”
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A multistrategy improved hunger games search algorithm by Qiu Yihui, Zhang Xinqiang, Li Ruoyu, Li Dongyi, Xia Feihan

“…The proposed MHGS algorithm provides a novel and effective framework for solving complex optimization problems, demonstrating significant theoretical and practical value in the field of computational intelligence.…”
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Intelligent monitoring and control of farmland based on edge-cloud collaboration and digital twin for digital energy management: investment benefit analysis by Zheng Liu

“…In terms of intelligent control, deep reinforcement learning is used to optimize irrigation decision-making, and adaptive algorithms are combined to improve the flexibility of agricultural equipment scheduling. …”
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A surrogate-assisted differential evolution algorithm with a dual-space-driven selection strategy for expensive optimization problems by Hanqing Liu, Zhigang Ren, Chenlong He, Wenhao Du

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Approach to knowledge management and the development of a multi-agent knowledge representation and processing system by E. I. Zaytsev, E. V. Nurmatova

“…Methods for distribution of intelligent software agents on the MKRPS nodes are proposed along with algorithms for optimizing the logical structure of the distributed knowledge base (DKB) to improve the performance of the MKRPS in terms of volume, cost and time criteria.Conclusions. …”
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A Bi-Level Capacity Optimization Method for Hybrid Energy Storage Systems Combining the IBWO and MVMD Algorithms by Qiaoqiao Xing, Shidong Li, Da Qiu, Yang Long, Qinyi Liao, Xiangjin Yin, Yunxiang Li, Kai Qian

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Consensus artificial intelligence-driven prognostic signature for predicting the prognosis of hepatocellular carcinoma: a multi-center and large-scale study by Wen Wen, Rui Wang

“…This study developed a consensus artificial intelligence-derived prognostic signature (CAIPS) by integrating ten machine learning algorithms (101 methods) across six multi-center HCC cohorts (n = 1110). …”
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Optimization method for educational resource recommendation combining LSTM and feature weighting by Meixia Yang

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