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  1. 101

    Multi-Objective Optimization Scheduling of a Wind–Solar Energy Storage Microgrid Based on an Improved OGGWO Algorithm by Dong Mo, Qiuwen Li, Yan Sun, Yixin Zhuo, Fangming Deng

    Published 2025-01-01
    “…To achieve the optimal solution between construction costs and carbon emissions in the multi-target optimization scheduling, this paper proposes a multi-objective optimization scheduling design for wind–solar energy storage microgrids based on an improved oppositional gradient grey wolf optimization (OGGWO) algorithm. …”
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    Article
  2. 102

    Research on Collaborative Optimization Method of CCHP Regional Integrated Energy System Based on Improved Multivariate Universe Algorithm by Dahai Xu, Changle Yu, Wenwen Li, Su Zhang, Zhengda Li, Zhihui Qu, Pengtao Li, Xingfan Han

    Published 2025-01-01
    “…A case study conducted in a representative northern region yielded the following experimental results: When compared with both the traditional particle swarm algorithm and an improved version of it, the CCHP-type integrated energy system optimized using the enhanced multi-objective multiverse algorithm reduced operating costs by 7.98% and carbon dioxide emissions by 12%, relative to the original system. …”
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  3. 103

    Optimization of CO2 water-alternating-gas injection parameters based on an improved hunger game search algorithm by WU Gongyi, SUN Yuxin, SUN Xiaofei, JI Hongming, ZHANG Yanyu

    Published 2025-06-01
    “…The hunger game search algorithm improved by the Tent chaotic mapping function is an effective method for optimizing CO2 WAG injection parameters. …”
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    Article
  4. 104
  5. 105

    Application of improved ant-lion algorithm for power systems. by Wenjing Wang, Renjun Zhou

    Published 2024-01-01
    “…The required number of iterations was significantly better than other algorithms. In the verification of solving economic load dispatch, the improved ant-lion optimizer achieved a total fuel cost reduction of 0.10% -2.39% and 6% in both 3-unit and 6-unit simulations, respectively, compared to the other three algorithms. …”
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    Article
  6. 106

    A Bi-Level Capacity Optimization Method for Hybrid Energy Storage Systems Combining the IBWO and MVMD Algorithms by Qiaoqiao Xing, Shidong Li, Da Qiu, Yang Long, Qinyi Liao, Xiangjin Yin, Yunxiang Li, Kai Qian

    Published 2025-04-01
    “…The outer layer minimizes the annual total cost through the application of an Improved Beluga Whale Optimization (IBWO) algorithm, which is enhanced by strategies including the reverse elitism strategy, horizontal and vertical crossover operations, and a whirlwind scavenging strategy to improve performance. …”
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  7. 107
  8. 108

    Research on Cold Chain Logistics Joint Distribution Vehicle Routing Optimization Based on Uncertainty Entropy and Time-Varying Network by Huaixia Shi, Yu Hong, Qinglei Zhang, Jiyun Qin

    Published 2025-05-01
    “…The solution combines simulated annealing strategies with genetic algorithms. It also uses the entropy mechanism to optimize uncertainties, improving global search performance. …”
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  9. 109
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  11. 111

    Optimizing Constrained Engineering Optimization Problems Using Improved Mountain Gazelle Optimizer by Vu Hong Son Pham, Nghiep Trinh Nguyen Dang, Van Nam Nguyen

    Published 2025-01-01
    “…This study introduces a novel approach to engineering design optimization through the development of an improved mountain gazelle optimizer (iMGO) that incorporates variable neighborhood search (VNS) techniques. …”
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  12. 112

    Road damage detection based on improved YOLO algorithm by Luyao Ma, Ming Chen

    Published 2025-08-01
    “…Experimental results show that compared to existing methods, this algorithm boosts the retrieval rate by 2.3%, increases the average value by 0.3, and improves the harmonic mean F1 by 0.7 relative to other models. …”
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  13. 113
  14. 114

    Enhanced zebra optimization algorithm for sustainable combined economic and emission dispatch in power systems by Ahmed Arkwazee, Rana Abttan

    Published 2025-09-01
    “…Experimental results show that IMZOA significantly reduces costs and emissions compared to established algorithms like LM and SA, and improved methods such as asinhCAOA, RLADE, and the standard Zebra Optimization Algorithm ZOA. …”
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  15. 115
  16. 116

    Site Selection Optimization Strategy for Independent Secondary Device Integrated Center Based on Improved Artificial Bee Colony Algorithm by Xiaoping XIONG, Shaolei HAO, Di SUN, Guangyang LIN, Hang LI

    Published 2021-09-01
    “…Firstly, the possible interval of the optimal solution is calculated with the improved artificial bee colony algorithm; and then the ISDIC site node that is most suitable for the center is obtained through precise calculations; and finally the practical engineering significance of the model and the superiority of the method are fully illustrated through analyzing the indexes of the optimal node.…”
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  17. 117

    Multi-Objective Scheduling Optimization of Prefabricated Components Production Using Improved Non-Dominated Sorting Generic Algorithm II by Yishi Zhao, Shaokang Du, Ming Tu, Haichuan Ma, Jianga Shang, Xiuqiao Xiang

    Published 2025-02-01
    “…Given the complex modeling and numerous constraints faced by the production of prefabricated components, we propose an improved Non-dominated Sorting Genetic Algorithm II (NSGA-II) for multi-objective optimization. …”
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  18. 118
  19. 119

    RETRACTED ARTICLE: Intelligent power management based on multi-objective cost function for plug-in biogas hybrid vehicles under uncertain driving conditions by Sameh Abd-Elhaleem, Walaa Shoeib, Abdel Azim Sobaih

    Published 2022-11-01
    “…The long-term power management depends on an improved generalized particle swarm optimization algorithm (IGPSO) to obtain the globally optimal values of motor and biogas engine torques. …”
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  20. 120

    Capacity optimization of photovoltaic storage hydrogen power generation system with peak shaving and frequency regulation by Dan Yu, Peng Yang, Weijun Zhu

    Published 2025-01-01
    “…The experimental results show that this method can obtain the best capacity allocation result based on local lighting conditions and the cost of the power generation system, whereas the improved particle swarm optimization algorithm can solve the model faster and reduce the cost of the power generation system. …”
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    Article