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  1. 201

    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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  2. 202

    Polar lights optimizer: A novel algorithm for accurate parameter estimation in proton exchange membrane fuel cells by Mohammad Aljaidi, Pradeep Jangir, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Ali Fayez Alkoradees, Mohammad Khishe, Reena Jangid

    Published 2025-09-01
    “…The PLO algorithm generates SSE results of 0.025493 for BCS 500 W and 0.275211 for Nedstack 600 W PS6 and 0.283774 for STD 250 W Stack while keeping AE at 0.259293 and RE% at 1.185075 for the STD 250 W Stack. …”
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  3. 203

    Portfolio Optimization with Artificial Hummingbird Algorithm for Cement Industry by Murat Erhan Çimen

    Published 2024-12-01
    “…Portfolio optimization, which is performed while investing in any asset, is an important issue for all investors and finance researchers. …”
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  4. 204

    An optimal L∞-PLA algorithm for trajectory data compression by ZHAO Huanyu, SUN Guohao, LI Tongliang, YANG Jian, PANG Chaoyi

    Published 2024-09-01
    “…MDisPLA used a divide-and-conquer strategy to extend the one-dimensional optimal PLA algorithm for optimizing compression of multi-dimensional trajectory data. …”
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  5. 205

    Multi-strategy collaborative optimization of gravitational search algorithm by Zhonghua Yang, Yuanli Cai, Ge Li, Peng Wang, Yu Chen

    Published 2025-08-01
    “…In the early iterations, particle positions are primarily updated using the original gravitational force, preserving the inherent characteristics of the gravitational search algorithm. In the later stages, particles with better fitness values are updated using a globally optimal Lévy random walk strategy to enhance local search capabilities, while particles with poorer fitness values are updated using the sparrow algorithm follower strategy. …”
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  6. 206

    Fast autoscaling algorithm for cost optimization of container clusters by José María López, Joaquín Entrialgo, Manuel García, Javier García, José Luis Díaz, Rubén Usamentiaga

    Published 2025-05-01
    “…In comparison to the heuristics, FCMA achieves similar solving times while consistently delivering more cost-effective solutions.…”
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  7. 207

    Optimization of the Weight Processing Algorithm in Multichannel Doppler Filtering by V. I. Koshelev, Ngoc Hieu Trinh

    Published 2024-05-01
    “…An MDF synthesis was carried out using optimization procedures, and the effectiveness of the algorithms was assessed using computer calculations.Results. …”
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  8. 208

    Multiple strategy enhanced hybrid algorithm BAGWO combining beetle antennae search and grey wolf optimizer for global optimization by Fan Zhang, Chuankai Liu, Peng Liu, Shuiting Ding, Tian Qiu, Jiajun Wang, Huipeng Du

    Published 2025-05-01
    “…Abstract This study proposes BAGWO, a novel hybrid optimization algorithm that integrates the Beetle Antennae Search algorithm (BAS) and the Grey Wolf Optimizer (GWO) to leverage their complementary strengths while enhancing their original strategies. …”
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  9. 209
  10. 210

    Mixed Multi-Strategy Improved Aquila Optimizer and Its Application in Path Planning by Tianyue Bao, Jiaxin Zhao, Yanchang Liu, Xusheng Guo, Tianshuo Chen

    Published 2024-12-01
    “…Traditional Aquila Optimizers, while effective, face limitations such as uneven population initialization, a tendency to get trapped in local optima, and slow convergence rates. …”
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  11. 211

    Application of improved particle swarm optimization algorithm combined with genetic algorithm in shear wall design by Wei Gao

    Published 2025-12-01
    “…The example results show that when using the designed shear wall design program for scheme design, the success rate reaches 100 %, which is 38.47 % higher than the original particle swarm optimization algorithm. The obtained optimization scheme has interlayer displacement angles of 1/2096 and 1/1800 in the vertical and horizontal directions, respectively, while the torsional displacement ratio in both directions is 1.0908 and the torsional period ratio is 0.7125. …”
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  12. 212
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  14. 214

    Memetic Salp Swarm Algorithm for economic load dispatch problems by Mohammed A. Awadallah, Mohammed Azmi Al-Betar, Malik Braik, Raed Abu Zitar, Khaled Assaleh, Mahmud Alkoffash, Qusai Yousef Shambour

    Published 2025-08-01
    “…This hybridization scheme is known as a memetic algorithm, where SSA serves as a natural selection agent (general refinement) in a genotype environment, while A $$\beta$$ HCO serves as a culture selection agent (local refinement) in a phenotype environment. …”
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  15. 215

    Surrogate-assisted global and distributed local collaborative optimization algorithm for expensive constrained optimization problems by Xiangyong Liu, Zan Yang, Jiansheng Liu, Junxing Xiong, Jihui Huang, Shuiyuan Huang, Xuedong Fu

    Published 2025-01-01
    “…Abstract This paper presents a surrogate-assisted global and distributed local collaborative optimization (SGDLCO) algorithm for expensive constrained optimization problems where two surrogate optimization phases are executed collaboratively at each generation. …”
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  16. 216

    APPLICATION OF QUADRATIC PROGRAMMING ON PORTFOLIO OPTIMIZATION USING WOLFE’S METHOD AND PARTICLE SWARM OPTIMIZATION ALGORITHM by Syaripuddin Syaripuddin, Fidia Deny Tisna Amijaya, Wasono Wasono, Shanaz Tulzahrah, Rara Suciati

    Published 2024-05-01
    “…In this research, the classical method uses Wolfe’s method, while the heuristic method uses the particle swarm optimization (PSO) algorithm. …”
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  17. 217

    Multi strategy Horned Lizard Optimization Algorithm for complex optimization and advanced feature selection problems by Marwa M. Emam, Mosa E. Hosney, Reham R. Mostafa, Essam H. Houssein

    Published 2025-06-01
    “…The Horned Lizard Optimization Algorithm (HLOA) is a nature-inspired metaheuristic that mathematically mimics the adaptive defense mechanisms of horned lizards, including crypsis, skin color modulation, blood-squirting, and escape movements. …”
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  18. 218

    Well Pattern optimization as a planning process using a novel developed optimization algorithm by Seyed Hayan Zaheri, Mahdi Hosseini, Mohammad Fathinasab

    Published 2024-11-01
    “…The results indicate that while the genetic algorithm and particle swarm optimization do not guarantee optimal outcomes, the newly developed algorithm outperforms both methods. …”
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  19. 219

    Appraising the Pile Settlement Rates by Support Vector Regression Optimized Using the Novel Optimization Algorithms by Argyros Maris

    Published 2023-06-01
    “…Biogeography-Based Optimization (BBO) and Flow Direction Algorithm (FDA) were coupled with SVR to create the SVR-FDA and SVR-BBO frameworks. …”
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  20. 220

    Renewable energy forecasting using optimized quantum temporal model based on Ninja optimization algorithm by Mona Ahmed Yassen, El-Sayed M. El-kenawy, Mohamed Gamal Abdel-Fattah, Islam Ismael, Hossam El.Deen Salah Mostafa

    Published 2025-04-01
    “…Experimental implementation revealed that incorporating the Ninja Optimization Algorithm with the QTM model delivered the best R2 performance at 95.15% with an exceptional RMSE value of 0.00003, thus establishing its ability to optimize renewable energy forecasting accuracy.…”
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