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  1. 621

    Mathematical Formalization and Algorithmization of the Main Modules of Organizational and Technical Systems by A. A. Solodov

    Published 2020-09-01
    “…This mathematical interpretation of the organizational and technical systems structure allowed us to formalize the main problems solved by typical organizational and technical systems and consider optimal algorithms for solving such problems. The assumption when considering the problems of synthesis of optimal algorithms is to optimize the status assessment module of organizational and technical systems and the control module separately, while the main attention is paid to the consideration of optimal estimation algorithms. …”
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  2. 622

    Boosting feature selection efficiency with IMVO: Integrating MVO and mutation-based local search algorithms by Maryam Askari, Farid Khoshalhan, Hodjat Hamidi

    Published 2025-06-01
    “…In this research, we introduce the Improved Multi-Verse Optimizer (IMVO) algorithm, a novel feature selection method that integrates the Multi-Verse Optimizer (MVO) with local search algorithms (LSAs). …”
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  3. 623

    The Optimal Cost Design of Reinforced Concrete Beams Using an Artificial Neural Network—The Effectiveness of Cost-Optimized Training Data by Jaemin So, Seungjae Lee, Jonghyeok Seong, Donwoo Lee

    Published 2025-05-01
    “…This study presents a method for the automated design of reinforced concrete (RC) beam cross-sections using an artificial neural network (ANN) trained with cost-optimized data generated by the crow search algorithm (CSA). …”
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  4. 624

    Differential evolution-optimized gold nanorods for enhanced photothermal conversion by Aimad Koulali, Piotr Radomski, Paweł Ziółkowski, Francesca Petronella, Luciano De Sio, Dariusz Mikielewicz

    Published 2025-03-01
    “…Utilizing the Differential Evolution (DE) algorithm, a robust metaheuristic optimization approach, we calculated the optimal size and shape of AuNRs for selected wavelengths. …”
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  5. 625

    A novel transcendental metaphor metaheuristic algorithm based on power method by Huiying Zhang, Hanshuo Wu, Yifei Gong, Xiao Pan, Qipeng Zhong

    Published 2025-07-01
    “…Abstract This paper proposes a novel metaheuristic algorithm-the Power Method Algorithm (PMA), which is inspired by the power iteration method to solve complex optimization problems. …”
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  6. 626

    Multicluster Distributed Optimization Strategy for Turbine Wake Environment by Zhenping Yu, Xinmeng Zhou, Yedong Huang, Kunyu Zhou, Guangming Cui, Juntian Qu

    Published 2025-08-01
    “…The experimental results demonstrate that the proposed algorithm can effectively improve the computational efficiency of wake optimization, while ensuring the effect of the wake optimization algorithm in actual wind farms as much as possible, which is more in line with the wake optimization needs of actual wind farms. …”
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  7. 627

    A novel meta-heuristic algorithm based on candidate cooperation and competition by Yue Cong, Bingnan Yang, Jie Wei

    Published 2025-07-01
    “…Abstract Traditional meta-heuristic algorithms are often inspired by natural phenomena or biological behaviors, while relatively few are based on human social behavior. …”
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    Article
  8. 628

    Enhancing Injector Performance Through CFD Optimization: Focus on Cavitation Reduction by Jose Villagomez-Moreno, Aurelio Dominguez-Gonzalez, Carlos Gustavo Manriquez-Padilla, Juan Jose Saucedo-Dorantes, Angel Perez-Cruz

    Published 2025-06-01
    “…The integration of optimization algorithms further enhances these processes by facilitating studies on mechanical behavior and accelerating iterative operations. …”
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    Article
  9. 629

    A computation offloading scheme for energy consumption optimization in Internet of vehicles by Wenxuan GAO, Xinjie YANG

    Published 2023-10-01
    “…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 (S<sup>2</sup>COS), 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 S<sup>2</sup>COS can meet the latency requirements for computation-intensive and latency-sensitive tasks, while significantly reducing system energy consumption.…”
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  10. 630

    Application of Hybrid Algorithm with Large Data in Wind Farm Modeling by GUO Min, ZHAO Qiao-e, GAO Jin-cheng, ZHOU Bin-long

    Published 2019-02-01
    “…The real operation data of large-scale wind farm are analyzed and modeled by using the optimized particle swarm K-means hybrid clustering algorithm. …”
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  11. 631

    Solving Spatial Optimization Problems via Lagrangian Relaxation and Automatic Gradient Computation by Zhen Lei, Ting L. Lei

    Published 2025-01-01
    “…By automating the (sub)gradient computation, we significantly lower the cost of developing a Lagrangian algorithm for the <i>p</i>-median. And such automation can be applied to numerous other optimization problems.…”
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  14. 634

    Optimizing energy efficiency and indoor thermal comfort in rural self-built housing: A comparative study of GA and EA algorithms by Chen Chen, Yuanyuan Wei

    Published 2025-09-01
    “…This study investigates how building design parameters influence electricity consumption, CO2 emissions, and indoor thermal comfort, and compares the performance of Genetic Algorithm (GA) and Evolutionary Algorithm (EA) in optimizing these objectives. …”
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  15. 635

    Hybrid Improved PSO Algorithm for Soil Property Parameter Estimation by Mude Li, Aiping Shi, Yefan Shi, Tao Zhang, Cu Qu, Lihua Ye

    Published 2025-04-01
    “…For multimodal functions (e.g., F3), PSO-EDO significantly outperforms PSO-WOA (Particle Swarm Optimization-Whale Optimization Algorithm) with a 22.3% reduction in error. …”
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  16. 636

    Smart village construction and college students’ skills entrepreneurship path based on LSTM and simulated annealing algorithm by Xueli Dong

    Published 2025-07-01
    “…In addition, the LSTM is suitable for processing time series data and can effectively analyze the development and changes of smart rural construction, while the simulated annealing algorithm can efficiently find a near-optimal solution to optimize the entrepreneurial path. …”
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  17. 637
  18. 638

    A Ultra-Low Cost and Accurate AMC Algorithm and Its Hardware Implementation by Yuqin Zhao, Tiantai Deng, Bill Gavin, Edward A. Ball, Luke Seed

    Published 2025-01-01
    “…In this design, the CAMC algorithm is optimized to fit the FPGA characteristics to further improve the performance, and the computing demands of which could be saved over 94&#x0025; compared with other state-of-the-art designs. …”
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  19. 639

    Dynamic arithmetic optimization algorithm control of distributed generations for demand balancing and enhancing power quality of unbalanced distribution systems by Ahmad Eid, Abdulrahman Alsafrani

    Published 2024-12-01
    “…Each system phase has its own DG. Particle Swarm Optimization (PSO) and Dynamic Arithmetic Optimization Algorithm (DAOA) determine each phase’s best locations, sizes, and power factors. …”
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  20. 640

    Mcaaco: a multi-objective strategy heuristic search algorithm for solving capacitated vehicle routing problems by Yanling Chen, Jingyi Wei, Tao Luo, Jie Zhou

    Published 2025-03-01
    “…Through a series of experiments, it is demonstrated that compared to multi-objective particle swarm optimization (MOPSO), non-dominated sorting genetic algorithm II (NSGA-II), and multi-objective sparrow search algorithm (MOSSA), the proposed MCAACO significantly reduces travel paths by an average of 3.05% and increases vehicle service coverage by an average of 3.2%, while satisfying vehicle capacity constraints. …”
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