Showing 21 - 40 results of 5,934 for search '(( whole (optimizer OR optimize) algorithm ) OR ( while (optimizer OR optimize) algorithm ))', query time: 0.34s Refine Results
  1. 21

    Integrated Optimization of Pipe Routing and Clamp Layout for Aeroengine Using Improved MOALO by Qiang Liu, Zhi Tang, Huijuan Liu, Jiapeng Yu, Hui Ma, Yonghua Yang

    Published 2021-01-01
    “…To this end, the MOALO (multiobjective ant lion optimizer) algorithm is modified by introducing the levy flight strategy to improve the global search performance and convergence speed, and it is further used as a basic computation tool. …”
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  2. 22

    A comprehensive review of artificial intelligence approaches for smart grid integration and optimization by Malik Ali Judge, Vincenzo Franzitta, Domenico Curto, Andrea Guercio, Giansalvo Cirrincione, Hasan Ali Khattak

    Published 2024-10-01
    “…An efficient Energy Management System (EMS) is essential to deal with uncertainties associated with renewable energy production and load demand while optimizing the operation of distributed energy generation sources. …”
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  3. 23

    Diesel Engine Urea Injection Optimization Based on the Crested Porcupine Optimizer and Genetic Algorithm by Xu Chen, Changhai Ma, Quanli Dou, Shuzhan Bai, Ke Sun, Zhenguo Li

    Published 2025-05-01
    “…Finally, the Nondominated Sorting Genetic Algorithm II (NSGA-II) was used to optimize the urea injection volume for all conditions. …”
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  4. 24

    Sigmoid-Function-Based Adaptive Pelican Optimization Algorithm for Global Optimization by A. F. S. Yussif, S. Adjei, B. E. Wilson

    Published 2025-03-01
    “… This paper introduces the Sigmoid-function-based Adaptive Pelican Optimization Algorithm (MPOA), an enhanced version of the traditional Pelican Optimization Algorithm (POA) aimed at improving the POA's performance. …”
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  5. 25

    RRT-Based Optimizer: A Novel Metaheuristic Algorithm Based on Rapidly-Exploring Random Trees Algorithm by Guang-Jin Lai, Tao Li, Bao-Jun Shi

    Published 2025-01-01
    “…Real-world optimization problems are becoming increasingly complex and require effective and versatile algorithms to provide reliable solutions. …”
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  6. 26

    Opportunistic spectrum sharing protocol and optimal resource allocation based on OFDM cooperation relaying by Wei-dang LU, Xuan-li WU, Xue-jun SHA, Nai-tong ZHANG

    Published 2012-11-01
    “…An opportunistic spectrum sharing protocol based on OFDM cooperation relaying was proposed.When the primary user experiences weak channel conditions,it could not achieve its target rate.If the cognitive user could help the primary user achieve its target rate,it accessed the pectrum of the primary user in the cooperation way.In this access way,the cognitive user used a fraction of the subcarriers to amplify-and-forward the signal of the primary user,to help the primary user achieve its target rate.And uses the remained subcarriers to transmit its own signal.The resource allocation was analyzed in this cooperation way.An optimal resource allocation algorithm based on dual ethod was proposed,which maximized the rate of the cognitive user while g anteeing the primary user achieve its target rate.If the cognitive user could not help the primary user achieve its target rate,to make use the spectrum efficiently,the cognitive user accessed the spectrum of the primary user in the non-cooperation way,and uses the whole accessed spectrum to transmit its own signal.The simulation demonstrates the efficiency of the proposed spectrum sharing protocol as well as its benefit to both primary and cognitive user.…”
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  7. 27

    Optimizing Pile Bearing Capacity Prediction Using Specific Random Forest Models Optimized by Meta-Heuristic Algorithms for Enhanced Geomechanically Applications by Nengyuan Chen

    Published 2023-12-01
    “…To achieve highly accurate predictions of Pile Bearing Capacity (PBC), the study employs a cutting-edge approach featuring Specific Random Forest (RF) prediction models, strategically enhanced with two potent meta-heuristic algorithms: the Snake Optimizer (SO) and the Equilibrium Optimizer (EO). …”
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  8. 28

    Hierarchical multi step Gray Wolf optimization algorithm for energy systems optimization by Idriss Dagal, AL-Wesabi Ibrahim, Ambe Harrison, Wulfran Fendzi Mbasso, Ahmad O. Hourani, Ievgen Zaitsev

    Published 2025-03-01
    “…Abstract Gray Wolf Optimization (GWO), inspired by the social hierarchy and cooperative hunting behavior of gray wolves, is a widely used metaheuristic algorithm for solving complex optimization problems in various domains, including engineering design, image processing, and machine learning. …”
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  9. 29

    “Optimizing the Optimization”: A Hybrid Evolutionary-Based AI Scheme for Optimal Performance by Agathoklis A. Krimpenis, Loukas Athanasakos

    Published 2025-03-01
    “…This collaborative process seeks to achieve optimal solutions at reduced convergence costs. This mixed scheme was tested on challenging benchmark functions, demonstrating convergence speeds that were at least three times faster than the best-performing standalone algorithms while maintaining solution quality. …”
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  10. 30

    Research of the Parameter Comprehensive Optimization of Excavator Working Device based on the Hybrid Optimization Algorithm by Zhang Xian, Liu Baixi, Qu Tao

    Published 2016-01-01
    “…The parameter of working device in the anti shovel hydraulic excavator are integrated optimized by using the hybrid algorithm of simulated annealing and penalty function. …”
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  11. 31

    Statistical Analysis Method for Optimal Prameters of Telemetry Communication by XIE Jun, WU Sailong, HAO Hang, ZHANG Songwei, WU Ruiqing, SUN Xiangyang

    Published 2025-06-01
    “…In order to improve the performance of telemetry of logging while drilling (TLWD) in complex drilling environment, the telemetry communication system is developing towards the trend of multi-architecture, multi-modal and multi-method, which brings a complication and inefficiency in the processing of selecting the optimal communication parameters. …”
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  12. 32

    Multiplier leadership optimization algorithm (MLOA): unconstrained global optimization approach for melanoma classification by Sukanta Ghosh, Amar Singh, Shakti Kumar

    Published 2025-06-01
    “…Abstract This paper proposes the multiplier leadership optimization algorithm, which draws inspiration from multiplier leadership principles to search for and optimize solutions to complex problems effectively. …”
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  13. 33

    Optimal Placement of Phasor Measurement Unit in Electrical Grid Using Dingo Optimization Algorithm by ARIYO Funso Kehinde, AYANLADE Samson Oladayo, JIMOH Abdulrasaq, ADEBAYO Moses Taiwo

    Published 2025-05-01
    “…The study utilizes the Dingo Optimization Algorithm, a metaheuristic inspired by nature, to identify the best PMU placement. …”
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  14. 34

    A new human-based offensive defensive optimization algorithm for solving optimization problems by Ning Fang, Cheng Xu, Xuxiong Gong, Zhouhua Wu

    Published 2025-04-01
    “…Abstract A novel human-inspired metaheuristic algorithm, termed Offensive Defensive Optimization, has been introduced to address single-objective optimization problems. …”
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  15. 35

    Comparative Review of Multi-Objective Optimization Algorithms for Design and Safety Optimization in Electric Vehicles by I Gede S. S. Dharma, Rachman Setiawan

    Published 2024-01-01
    “…Despite the widespread use of established optimization algorithms like Non-Dominated Sorting Genetic Algorithm-II (NSGA-II), Non-Dominated Sorting Genetic Algorithm-III (NSGA-III), and Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) in real-world engineering optimization problems, newer algorithms such as Two-Stage NSGA-II (TS-NSGA-II), Dynamic Constrained NSGA-III (DCNSGA-III), MOEA/D with Virtual Objective Vectors (MOEA/D-VOV), Large-Scale Evolutionary Multi-Objective Optimization Assisted by Directed Sampling (LMOEA-DS), and Super-Large-Scale Multi-Objective Evolutionary Algorithm (SLMEA) remain underexplored in the context of Battery Electric Vehicle (BEV) safety, particularly in optimizing complex, non-linear, and constrained multi-objective problems like crashworthiness and thermal management. …”
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  16. 36
  17. 37

    Minimum-cost network hardening algorithm based on stochastic loose optimize strategy by Guang-sheng ZHAO, Qing-feng CHENG, Yong-lin SUN

    Published 2015-01-01
    “…To construst a minimum-cost network hardening (MCNH) scheme in large-scale network,a stochastic loose optimize strategy based algorithm (MCNHA-SLOS) was proposed,and its effectiveness was analyzed.MCNHA-SLOS was a near-optimal approximation algorithm,which could achieve iterative computations in the array of sparse spaces of the whole plan space,so that the near-optimal scheme must exist in the low cost plan space.Instantiation analysis and experimental results show that the MCNHA-SLOS algorithm to be efficient,precision controllable and asymptotically optimal,and thus very applicable for large-scale network.…”
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  18. 38

    Application of Improved Whale Algorithm to Optimize Dephosphorization Process Parameters in Converter Steelmaking by Congrui Wu, Yueping Kong

    Published 2025-04-01
    “…This study addresses process parameter optimization challenges in converter steelmaking by proposing an improved multi-objective whale optimization algorithm (IMOWOA) that synergistically integrates metallurgical thermodynamics with data-driven modeling. …”
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  19. 39

    Genetic Algorithms Applied to Optimize Neural Network Training in Reference Evapotranspiration Estimation by Eluã Ramos Coutinho, Jonni G.F. Madeira, Robson Mariano da Silva, Angel Ramon Sanchez Delgado, Alvaro L.G.A. Coutinho

    Published 2025-04-01
    “…This confirms that employing Genetic Algorithms (GA) to automate the training and optimization of the model is effective and enhances the neural network's capacity to predict ETo.…”
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  20. 40

    Multi-strategy enterprise development optimizer for numerical optimization and constrained problems by Xinyu Cai, Weibin Wang, Yijiang Wang

    Published 2025-03-01
    “…However, the analysis of the EDO algorithm shows that it suffers from the defects of rapidly decreasing population diversity and weak exploitation ability when dealing with complex optimization problems, while its algorithmic structure has room for further enhancement in the optimization process. …”
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