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  1. 141

    Two-Stage Genetic Algorithm for Optimization Logistics Network for Groupage Delivery by Ivan P. Malashin, Vadim S. Tynchenko, Igor S. Masich, Denis A. Sukhanov, Daniel A. Ageev, Vladimir A. Nelyub, Andrei P. Gantimurov, Alexey S. Borodulin

    Published 2024-12-01
    “…This study explored the optimization of groupage intercity delivery using a two-stage genetic algorithm (GA) framework, developed with the BaumEvA Python library. …”
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    Article
  2. 142

    The WSN Localization Algorithm Integrating Ranging Correction and Spider Wasp Optimization by YU Xiu-wu, XIAO Lin, LIU Yong, YE Lai

    Published 2025-01-01
    “…This paper proposes a modified DV-Hop algorithm that integrates distance correction and a Spider Wasp Optimization (SWO) algorithm to address these issues. …”
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  3. 143

    Damage Detection of Steel Roof Systems Using Planet Optimization Algorithm by Thanh Sang-To, Van The Huy-Nguyen, Samir Khatir, The Vi-Huynh, Hoang Le-Minh, Thanh Cuong-Le

    Published 2025-10-01
    “…The achieved results illustrate that in terms of stability, robustness, and quality of the obtained solution, POA is one of most outstanding optimization algorithms. POA ranks No. 1 in functions F1, F4, F7, F8, F13, while POA is highly ranked and sufficiently competitive with the other contenders in the rest of tests. …”
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  4. 144
  5. 145

    Optimization of the Offshore Wind Turbines Layout Using Cuckoo Search Algorithm by Ibrahim Abdulwahab, Solomon Andrew Onazi, Gideon Rimamfate, Akande Abdulwasiu, Abubakar Umar, N.A Iliyasu

    Published 2024-06-01
    “…After-which a cuckoo search algorithm technique is employed in the wind farm model to optimize the optimization problem (minimizing the wake effect while improving power output and cost). …”
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  6. 146

    Optimal performance design of bat algorithm: An adaptive multi‐stage structure by Helong Yu, Jiuman Song, Chengcheng Chen, Ali Asghar Heidari, Yuntao Ma, Huiling Chen, Yudong Zhang

    Published 2025-06-01
    “…Abstract The bat algorithm (BA) is a metaheuristic algorithm for global optimisation that simulates the echolocation behaviour of bats with varying pulse rates of emission and loudness, which can be used to find the globally optimal solutions for various optimisation problems. …”
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  7. 147

    Causal Diagnosability Optimization Design for UAVs Based on Maximum Mean Covariance Difference and the Gray Wolf Optimization Algorithm by Xuping Gu, Xianjun Shi

    Published 2025-05-01
    “…Finally, a diagnosability optimization technique utilizing the GWO algorithm is proposed. …”
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  8. 148

    Investigation of a Multi-Strategy Ensemble Social Group Optimization Algorithm for the Optimization of Energy Management in Electric Vehicles by Aala Kalananda Vamsi Krishna Reddy, Komanapalli Venkata Lakshmi Narayana

    Published 2022-01-01
    “…A multi-strategy ensemble social group optimization algorithm (ME-SGO) to improve the exploration for complex and composite landscapes through distance-based strategy adaption and success-based parameter adaption while incorporating linear population reduction is proposed. …”
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  9. 149

    Scheduling optimization based on particle swarm optimization algorithm in emergency management of long-distance natural gas pipelines. by Huichao Guo, Runhua Huang, Shuqin Cheng

    Published 2025-01-01
    “…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …”
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    Article
  10. 150

    An Improved Particle Swarm Optimization Algorithm forOptimal Allocation of Distributed Generation Units in Radial Power Systems by Neda Hantash, Tamer Khatib, Maher Khammash

    Published 2020-01-01
    “…The minimum value of fitness losses using the applied algorithm is found to be 0.0.0406 while the average elapsed time is 62.2325 s. …”
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  11. 151

    Optimal adaptive heuristic algorithm based energy optimization with flexible loads using demand response in smart grid. by Hisham Alghamdi, Lyu-Guang Hua, Ghulam Hafeez, Sadia Murawwat, Imen Bouazzi, Baheej Alghamdi

    Published 2024-01-01
    “…MATLAB is used to do a load scheduling simulation for home appliances based on the OAWDO algorithm. By contrasting it with other algorithms, including the genetic algorithm (GA), the whale optimization algorithm (WOA), the fire-fly optimization algorithm (FFOA), and the wind-driven optimization (WDO) algorithms, the effectiveness of the OAWDO technique is supported. …”
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  12. 152

    RUL Prediction of Rolling Bearings Based on Fruit Fly Optimization Algorithm Optimized CNN-LSTM Neural Network by Jiaping Shen, Haiting Zhou, Muda Jin, Zhongping Jin, Qiang Wang, Yanchun Mu, Zhiming Hong

    Published 2025-02-01
    “…In addition, introducing FOA enables the model to dynamically adjust the hidden layers and thresholds while optimizing the optimal path, thereby finding the best solution. …”
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  13. 153

    Optimized conductor selection and phase balancing in unbalanced distribution networks: Economic optimization via the vortex search algorithm by Brandon Cortés-Caicedo, Jhony Andrés Guzmán-Henao, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña, Rubén Iván Bolaños

    Published 2025-09-01
    “…This methodology is compared against the hurricane optimization algorithm, the sine cosine algorithm, and the salp swarm optimization algorithm. …”
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  14. 154

    Optimizing energy constrained target localization and tracking with radial bias and seeker optimization algorithms in wireless sensor networks by S. Yazhinian, S. Famila, P. Jose, Mahendar A, Sofia R

    Published 2025-06-01
    “…This paper proposes a novel approach combining Radial Bias (RB) with the Seeker Optimization Algorithm (SOA) to address the challenges of energy-constrained target localization and tracking. …”
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  15. 155

    Energy-Efficient DC Power Traction Network Systems for Urban Mass Transportation: A Comparative Study of Optimization Algorithms by Dongxian Yu, Zhixin Wu, Lei Wang, Zaihui Cao, Hamdolah Aliev

    Published 2025-01-01
    “…To validate the proposed method, we compare the performance of the GWO algorithm with other optimization techniques, such as the Teaching-Learning-Based Optimizer (TLBO) and Differential Evolution (DE). …”
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  16. 156

    Many-Objective Cheetah Optimizer: A Novel Paradigm for Solving Complex Engineering Problems by Pinank Patel, Divya Adalja, Nikunj Mashru, Pradeep Jangir, Arpita, Reena Jangid, G. Gulothungan, Ahmad O. Hourani, Kaznah Alshammari

    Published 2025-06-01
    “…MaOCO represents the Many-Objective Cheetah Optimization Algorithm which draws its concepts from the hunting behavior of cheetahs. …”
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  17. 157
  18. 158

    Rethinking Metaheuristics: Unveiling the Myth of “Novelty” in Metaheuristic Algorithms by Chia-Hung Wang, Kun Hu, Xiaojing Wu, Yufeng Ou

    Published 2025-07-01
    “…While nature-inspired optimization methods show promise for various applications, their effectiveness is often limited by metaphor-driven design, structural biases, and a lack of sufficient theoretical foundation. …”
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  19. 159

    An improved dung beetle optimizer based on Padé approximation strategy for global optimization and feature selection by Tianbao Liu, Lingling Yang, Yue Li, Xiwen Qin

    Published 2025-03-01
    “…Feature selection is a crucial data processing method used to reduce dataset dimensionality while preserving key information. In this paper, we proposed a multi-strategy enhanced dung beetle optimization algorithm (mDBO) that integrates multiple strategies to effectively address the feature selection problem. …”
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  20. 160

    A novel robust multi-objective evolutionary optimization algorithm based on surviving rate by Wenxiang Jiang, Kai Gao, Shuwei Zhu, Lihong Xu

    Published 2025-02-01
    “…Despite the success of multi-objective evolutionary optimization algorithms in addressing complex optimization problems, research focusing on input disturbances remains limited. …”
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