Showing 261 - 280 results of 3,336 for search 'improve (((cost OR most) OR post) OR root) optimization algorithm', query time: 0.27s Refine Results
  1. 261

    Research on Vehicle Route Optimization for Half-Open Multi-Energy Urban Distribution Considering Order Priority by Mingxuan Zhang

    Published 2025-01-01
    “…On the basis of the sparrow search algorithm, Tent chaotic mapping is added and random key coding strategy is inserted for discretization, which increases the diversity of the initial population of the sparrow search algorithm and improves the algorithm’s global optimization seeking ability. …”
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  2. 262

    Residual Life Prediction of Proton Exchange Membrane Fuel Cell Based on Improved ESN by Tiejiang YUAN, Rongsheng LI, Jiandong KANG, Huaguang YAN

    Published 2025-05-01
    “…Aiming at the problem that the current residual effective life prediction (RUL) technique for proton exchange membrane fuel cells (PEMFCs) has poor prediction effect in the medium and long term, a residual life prediction method based on the Improved Gray Wolf Optimization algorithm (IGWO) and Echo State Network (ESN) is proposed, in which the voltage of the electric stack is firstly selected as a health indicator, and the PEMFC dataset is processed by using convolutional smoothing filtering method to carry out data Smoothing and normalization are used to effectively reduce the interference of outliers on the subsequent model training. …”
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  3. 263

    Two-Layer Optimal Scheduling and Economic Analysis of Composite Energy Storage with Thermal Power Deep Regulation Considering Uncertainty of Source and Load by Chao Xing, Jiajie Xiao, Xinze Xi, Jingtao Li, Peiqiang Li, Shipeng Zhang

    Published 2024-09-01
    “…The upper layer takes pumped storage as the optimization goal to improve net load fluctuation and the optimal peak load benefit; the lower layer takes the system’s total peak load cost as the optimization goal and obtains a day-before scheduling plan for the energy storage system, using an improved gray wolf algorithm to process it. …”
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  4. 264

    Long short‐term memory‐based forecasting of uncertain parameters in an islanded hybrid microgrid and its energy management using improved grey wolf optimization algorithm by Raji Krishna, Hemamalini S

    Published 2024-12-01
    “…Results demonstrate that the improved grey wolf optimization (IGWO) algorithm is more effective at reducing costs and provides faster optimal solutions.…”
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  5. 265

    Adaptive Multi-Objective Firefly Optimization for Energy-Efficient and QoS-Aware Scheduling in Distributed Green Data Centers by Ahmed Chiheb Ammari, Wael Labidi, Rami Al-Hmouz

    Published 2025-06-01
    “…To solve this, we propose an Adaptive Firefly-Based Bi-Objective Optimization (AFBO) algorithm that introduces multiple adaptive mechanisms to improve convergence and diversity. …”
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  6. 266

    Operation Optimization Strategy of Commercial Combined Electric Heating System Based on Particle Swarm Optimization Algorithm by WANG Qing, LI Congcong, WANG Pingxin, WU Qingqing, CAI Xiaoyu

    Published 2023-02-01
    “… In order to improve the energy efficiency of the electric heating system, a particle swarm optimization (PSO, Particle Swarm Optimization)-based operation optimization strategy for the direct storage combined electric heating system is proposed.A mathematical model of influencing factors inside and outside the walls of electric heating buildings is established, and the simulink toolbox in matlab is used to build the overall system under the premise of determining the quantity of electric heating.Combining demand response ideas, the objective function is to establish the minimum heating and electricity cost of the user, and different sub-modules are selected to form the control module to achieve simulation verification, and the inverse cosine method is used to update the improved particle swarm algorithm to update the learning factor to solve the set objective function.Finally, through a calculation example of electricity consumption data of an enterprise in Jinan, Shandong, comparing energy consumption and economy can be obtained: the total energy consumption throughout the day is lower than the actual energy consumption, and the electricity bill is reduced by 17.16% compared with the unoptimized time.…”
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  7. 267

    Optimal geometrical selection of skin mesh: experimental analysis and numerical optimization by Mehdi Khayami, Aisa Rassoli, Alireza Feizkhah

    Published 2025-07-01
    “…Hyperelastic properties of healthy and meshed skin were obtained through uniaxial tensile tests, and different geometries were analyzed using Abaqus. The optimal mesh geometry was then determined using genetic algorithms in Abaqus and MATLAB. …”
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  8. 268

    A new type of sustainable operation method for urban rail transit: Joint optimization of train route planning and timetabling by Guorong Fan, Chao Li, Xinyun Shao, Fangzheng Zhen, Yao Huang

    Published 2025-12-01
    “…To solve large-scale problems, an improved adaptive large neighborhood search algorithm (ALNS) is designed accordingly. …”
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  9. 269

    Edge server deployment decision based on improved NSGA-Ⅱ in the Internet of vehicles edge computing scenario by Sifeng ZHU, Yu WANG, Hao CHEN, Hai ZHU, Zhengyi CHAI, Chengrui YANG

    Published 2024-03-01
    “…In the context of the Internet of vehicles, the placement and deployment number of edge servers directly affect the efficiency of edge computing.Due to the high cost of deploying a large edge server on a macro base station and a base station, it can be complemented by deploying a small edge server on a micro base station, and the cost reduction needs to be optimized by optimizing the placement of large edge servers.In order to minimize the deployment cost and service delay of the edge server, and maximize the operator’s revenue and server load balance, the edge server placement problem combined with the vehicle networking user application service was modeled as a multi-objective optimization problem and a placement scheme based on improved NSGA-Ⅱ algorithm was proposed.The experimental results show that the proposed scheme can reduce the deployment cost of edge servers by about 44%, the latency by about 14.2%, and improve the revenue of operators by 24.2%, which has good application value.…”
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  10. 270

    Application of Swarm Intelligence Optimization Algorithm in Logistics Delivery Path Optimization under the Background of Big Data by Guofu Zhao

    Published 2023-01-01
    “…The hybrid algorithm can effectively improve the optimization efficiency of VRPTW, lay a foundation for solving large-scale VRPTW, and provide new research ideas and methods. …”
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  11. 271

    Loss reduction optimization strategies for medium and low-voltage distribution networks based on Intelligent optimization algorithms by Nian Liu, Yuehan Zhao

    Published 2024-11-01
    “…Methodology In order to reduce line losses, a loss optimization model for low and medium voltage distribution networks based on an improved Gray Wolf optimization support vector machine is proposed. …”
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  12. 272

    Forecasting Influenza Trends Using Decomposition Technique and LightGBM Optimized by Grey Wolf Optimizer Algorithm by Yonghui Duan, Chen Li, Xiang Wang, Yibin Guo, Hao Wang

    Published 2024-12-01
    “…Accurate influenza prediction is a critical issue in public health and serves as an essential tool for epidemiological studies. This paper seeks to improve the prediction accuracy of influenza-like illness (ILI) proportions by proposing a novel predictive model that integrates a data decomposition technique with the Grey Wolf Optimizer (GWO) algorithm, aiming to overcome the limitations of current prediction methods. …”
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  13. 273

    Comprehensive Study of Nonlinear Maglev System Utilizing COOT Optimized FOPID Controller by Marabathina Maheedhar, T. Deepa

    Published 2025-01-01
    “…To improve the performance of the magnetic levitation system, the most recent metaheuristic COOT algorithm was first employed in this study to tune the Fractional Order Proportional Integral and Derivative (FOPID) controller. …”
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  14. 274

    Optimizing Ontology Alignment through Improved NSGA-II by Yikun Huang, Xingsi Xue, Chao Jiang

    Published 2020-01-01
    “…Over the past decades, a large number of complex optimization problems have been widely addressed through multiobjective evolutionary algorithms (MOEAs), and the knee solutions of the Pareto front (PF) are most likely to be fitting for the decision maker (DM) without any user preferences. …”
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  15. 275

    Optimization of Wheel Reprofiling Based on the Improved NSGA-II by Xinghu Wang, Jiabin Yuan, Sha Hua, Bojia Duan

    Published 2020-01-01
    “…As a method to maintain the shape at the cost of the diameter size, reprofiling has significant impacts on the lifecycle of a train. …”
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  16. 276
  17. 277

    Optimizing grid-dependent and islanded network operations through synergic active-reactive power integration by Zohaib Hussain Leghari, Dalila Mat Said, Mazhar Baloch, Pervez Hameed Shaikh, Hafiz Mudassir Munir, Radomir Gono, Tomas Novak, Petr Moldrik

    Published 2024-12-01
    “…The first stage proposes an improved Jaya algorithm (IJaya) to optimize DG and SCB allocation during grid-connected operation, aiming to reduce power loss and improve voltage profiles. …”
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  18. 278
  19. 279

    APPLYING GRAPH THEORY TO OPTIMIZE PRODUCT DELIVERY ROUTES AND MINIMIZE COSTS IN THE RESTAURANT BUSINESS by Наталія Волосова, Наталія Стеблюк, Наталія Небаба, Олена Юдіна, Максим Корнєєв, Ганна Богородицька

    Published 2025-06-01
    “…Routing algorithms based on graphical description are considered the most optimal analysis method for developing optimal product delivery routes, which helps minimize enterprise costs. …”
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  20. 280

    Multi Objective Optimization of Electric Vehicle Charging Strategy Considering User Selectivity by Sheng Li, Xiangyu Yan, Guanhua Wang

    Published 2025-02-01
    “…To achieve this, an improved non-dominated sorting whale optimization algorithm (INSWOA) is proposed which initializes the population through logistic mapping, introduces nonlinear convergence factors for position updates, and uses adaptive inertia weights to improve population diversity, enhance global optimization ability, reduce premature convergence, and improve solution accuracy. …”
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