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  1. 1661

    Optimizing Competency-Based Human Resource Allocation in Construction Project Scheduling: A Multi-Objective Meta-Heuristic Approach by Bahman Shojaei, Heidar Dashti Naserabadi, Mohammad Javad Taheri Amiri

    Published 2024-09-01
    “…Our approach involves solving a sample problem precisely using GAMS software and developing two meta-heuristic algorithms—Non-Dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO). …”
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    Article
  2. 1662

    Control of steering wheel idle jitter based on optimization of engine suspension system with verifications using multi-sensor measurement by Shuilong He, Binqiang Chen, Zhansi Jiang, Yanxue Wang, Fuyun Liu

    Published 2018-06-01
    “…Parameters of the optimized suspension system were obtained by multi-objective particle swarm optimization. …”
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    Article
  3. 1663

    A New Framework for Dynamic Educational Marketing Segmentation in Student Recruitment: Optimizing Fuzzy C-Means with Metaheuristic Techniques by Rizal Bakri, Bobur Sobirov, Niken Probondani Astuti, Ansari Saleh Ahmar, Pawan Kumar Singh

    Published 2025-06-01
    “…However, the performance of FCM highly depends on determining parameters such as the number of clusters (k) and the level of fuzziness (m), which are not always optimal when determined manually. This study develops a new framework for dynamic educational marketing segmentation in student recruitment by optimizing FCM using three metaheuristic techniques: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Differential Evolution (DE). …”
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    Article
  4. 1664

    Resilient VPP cost optimization in DER-driven microgrids for large distribution systems considering uncertainty during extreme events by T.D. Suresh, M. Thirumalai, R. Hemalatha, Mohit Bajaj, Vojtech Blazek, Lukas Prokop

    Published 2025-07-01
    “…Simulation results demonstrate the BWO-based strategy’s superior performance, reducing total objective cost to $2.54 million, outperforming genetic algorithm (GA) and particle swarm optimization (PSO) by 5.01% and 8.54% respectively. …”
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    Article
  5. 1665

    A multi-objective master–slave methodology for optimally integrating and operating photovoltaic generators in urban and rural electrical networks by Jhony Andrés Guzmán-Henao, Rubén Iván Bolaños, Brandon Cortés-Caicedo, Luis Fernando Grisales-Noreña, Oscar Danilo Montoya, Jesús C. Hernández

    Published 2024-12-01
    “…Its master stage uses one out of three different algorithms—Multi-Objective Particle Swarm Optimization (MOPSO) algorithm, the Non-dominated Sorting Genetic Algorithm II (NSGA-II), or the Multi-Objective Ant Lion Optimizer (MOALO)—while the slave stage is always performed by a load flow analyzer. …”
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    Article
  6. 1666

    Integrating Machine Learning Workflow into Numerical Simulation for Optimizing Oil Recovery in Sand-Shale Sequences and Highly Heterogeneous Reservoir by Dung Bui, Abdul-Muaizz Koray, Emmanuel Appiah Kubi, Adewale Amosu, William Ampomah

    Published 2024-10-01
    “…The Artificial Neural Network (ANN) algorithm was found to provide higher field cumulative oil production compared with the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) of 3.5% and 26.5%, respectively. …”
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    Article
  7. 1667

    Research on optimal scheduling of minor and moderate floods for cascade reservoirs in the lower reaches of the jinsha river considering power generation by Zaimin Ren, Bin He, Chenchen Yao, Xiaoshuai Lv, Xihong Wang

    Published 2024-12-01
    “…The Multi-objective Particle Swarm Optimization (MOPSO) algorithm was used to find non-inferior solution sets. …”
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    Article
  8. 1668

    Internal sound field reconstruction method based on optimal arrangement of sound monitoring points near the cabin inner surface by Shengguo Shi, Qiang Guo, Huihui He, Xinyu Wang

    Published 2025-04-01
    “…Second, the modal confidence matrix is used as the objective function, and the position of acoustic monitoring points is optimized via quantum particle swarm optimization (QPSO). …”
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    Article
  9. 1669

    Enhancing Streamflow Prediction Accuracy: A Comprehensive Analysis of Hybrid Neural Network Models with Runge–Kutta with Aquila Optimizer by Rana Muhammad Adnan, Wang Mo, Ahmed A. Ewees, Salim Heddam, Ozgur Kisi, Mohammad Zounemat-Kermani

    Published 2024-11-01
    “…Abstract This study investigates the efficacy of hybrid artificial neural network (ANN) methods, incorporating metaheuristic algorithms such as particle swarm optimization (PSO), genetic algorithm (GA), gray wolf optimizer (GWO), Aquila optimizer (AO), Runge–Kutta (RUN), and the novel ANN-based Runge–Kutta with Aquila optimizer (LSTM-RUNAO). …”
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    Article
  10. 1670

    Peak-Valley difference based pricing strategy and optimization for PV-storage electric vehicle charging stations through aggregators by Qin Yan, Jinxin Wang, Tao Lin, Archie James Johnston

    Published 2025-08-01
    “…Using Multi-Objective Particle Swarm Optimization (MOPSO), the strategy thereby incorporates three main objectives; minimizing grid load fluctuations, maximizing aggregator profits, and reducing user costs. …”
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    Article
  11. 1671

    OPTIMIZING THE PLACEMENT OF A WORK-PIECE AT A MULTI-POSITION ROTARY TABLE OF TRANSFER MACHINE WITH VERTICAL MULTI-SPINDLE HEAD by N. N. Guschinski, V. E. Zdanovich, B. M. Rozin

    Published 2016-11-01
    “…To solve this problem the mathematical model and heuristic particle swarm optimization algorithm are proposed. …”
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    Article
  12. 1672

    An Optimization Strategy for Unit Commitment in High Wind Power Penetration Power Systems Considering Demand Response and Frequency Stability Constraints by Minhui Qian, Jiachen Wang, Dejian Yang, Hongqiao Yin, Jiansheng Zhang

    Published 2024-11-01
    “…To address the issue of accommodating large-scale wind power integration into the grid, a unit commitment model for power systems based on an improved binary particle swarm optimization algorithm is proposed, considering frequency constraints and demand response (DR). …”
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    Article
  13. 1673

    Optimal Operation Strategy of Cascade Hydro-Wind-Solar-Pumped Storage Complementary System Considering Flexible Regulation Ability by XIA Jinlei, TANG Yijie, WANG Lingling, JIANG Chuanwen, GU Jiu

    Published 2025-07-01
    “…To overcome the limitations of traditional models such as low predictive accuracy and the subjective selection of long short-term memory (LSTM) hyperparameters, the particle swarm optimization (PSO) algorithm is used to optimize the parameters of LSTM and the optimized LSTM model is then used to forecast the output of wind and solar power. …”
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    Article
  14. 1674

    Intrusion Detection Using Hybrid Pearson Correlation and GS-PSO Optimized Random Forest Technique for RPL-Based IoT by Wei Yang, Xinlong Wang, Zhiming Zhang, Shaolong Chen, Chengqi Hou, Siwei Luo

    Published 2025-01-01
    “…Second, we propose an efficient routing detection method that accelerates model training speed by using Hybrid Pearson Correlation and GS-PSO(Grid Search-Particle Swarm Optimization) Optimized Random Forest Technique. …”
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    Article
  15. 1675

    Tomato Yield Estimation Using an Improved Lightweight YOLO11n Network and an Optimized Region Tracking-Counting Method by Aichen Wang, Yuanzhi Xu, Dong Hu, Liyuan Zhang, Ao Li, Qingzhen Zhu, Jizhan Liu

    Published 2025-06-01
    “…The particle swarm optimization (PSO) algorithm was used to optimize the detection region, thus enhancing the counting accuracy. …”
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    Article
  16. 1676

    Optimal Dimensional Synthesis of Ackermann and Watt-I Six-Bar Steering Mechanisms for Two-Axle Four-Wheeled Vehicles by Yaw-Hong Kang, Da-Chen Pang, Dong-Han Zheng

    Published 2025-07-01
    “…This study investigates the dimensional synthesis of steering mechanisms for front-wheel-drive, two-axle, four-wheeled vehicles using two metaheuristic optimization algorithms: Differential Evolution with golden ratio (DE-gr) and Improved Particle Swarm Optimization (IPSO). …”
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    Article
  17. 1677
  18. 1678

    Two-Stage Collaborative Power Optimization for Off-Grid Wind–Solar Hydrogen Production Systems Considering Reserved Energy of Storage by Yiwen Geng, Qi Liu, Hao Zheng, Shitong Yan

    Published 2025-06-01
    “…Stage II employs an improved multi-objective particle swarm optimization (IMOPSO) algorithm to optimize HESS power allocation, minimizing unit hydrogen production cost and reducing average battery charge–discharge depth. …”
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    Article
  19. 1679

    Hybrid optimization for sustainable design and sizing of standalone microgrids integrating renewable energy, diesel generators, and battery storage with environmental consideration... by Mohd Bilal, Pitshou N. Bokoro, Gulshan Sharma

    Published 2025-03-01
    “…This study proposes the Hybrid Particle Whale Optimization Algorithm (HPWOA), combining Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA), to overcome the convergence issues of traditional methods. …”
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    Article
  20. 1680

    Theoretical framework to design and optimize feasible all optical modulator based on multi passband slit array filters in frequency domain by Mostafa Shabani, Gholamreza Karimi, Alvise Bagolini

    Published 2025-06-01
    “…Driven by the urgent need for high-performance optical filters and modulators in THz communication and imaging systems, this paper proposes an energy-efficient, high-modulation-depth all-optical modulator based on a plasmonic silicon-core slit array structure, along with methods for its design, fabrication, and optimization. The design process for tuning the number, resonance frequencies, amplitudes, and quality factors of the transmission passbands was based on a hybrid genetic particle swarm algorithm, employing both finite element method (FEM) and circuit modeling. …”
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    Article