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  1. 1081

    Bi-Level Collaborative Optimization for Medical Consumable Order Splitting and Reorganization Considering Multi-Dimensional and Multi-Scale Characteristics by Peng Jiang, Shunsheng Guo, Xu Luo

    Published 2025-07-01
    “…Subsequently, to solve this bi-level optimization problem, a hybrid bi-objective optimization algorithm is designed, integrating a collaborative iterative strategy to enhance solution efficiency and quality. …”
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    Article
  2. 1082

    Oral cancer detection via Vanilla CNN optimized by improved artificial protozoa optimizer by Yulong Chai, Xiuqing Chai, Lan Zhang, Gang Ye, Fatima Rashid Sheykhahmad

    Published 2025-08-01
    “…Due to its effectiveness in search space exploration while avoiding local optimal points, the IAPO algorithm is chosen to optimize the convolutional neural network. …”
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    Article
  3. 1083

    Establishment and Solution Test of Wear Prediction Model Based on Particle Swarm Optimization Least Squares Support Vector Machine by Xiao Huang, Yongguo Wang, Yuhui Mao

    Published 2025-03-01
    “…The model parameters are optimized by the two-dimensional coordinates (c and g) of the particle swarm algorithm to adapt to the given training sample set. …”
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    Article
  4. 1084
  5. 1085

    An enhanced alpha evolution moss growth optimizer for prognostic prediction in spontaneous intracerebral hemorrhage by Lingxian Hou, Yongsheng Wang, Xiuqi Lin, Chengye Li, Huangrong Guo, Congcong Jin, Yi Chen, Huiling Chen, Jing Ji, Wenzong Zhu

    Published 2025-05-01
    “…This study aims to improve SICH outcome prediction by developing the Alpha Evolution Moss Growth Optimization (AEMGO) algorithm for feature selection in high-dimensional medical datasets. …”
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    Article
  6. 1086

    Optimizing energy and CO2 efficiency in last-mile delivery using hybrid fleet models by Armin Mahmoodi, Leila Hashemi, Jeremy Laliberte, Seyed Mojtaba Sajadi

    Published 2025-12-01
    “…This study compares the environmental performance of hybrid and diesel trucks with quadcopter and fixed-wing remotely piloted aircraft systems (RPAS), employing a multi-objective optimization approach non-dominated sorting genetic algorithm II (NSGA-II) to identify optimal delivery routes balancing operational efficiency and sustainability. …”
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    Article
  7. 1087

    A novel research on network security situation prediction based on iteratively optimized RBF-NN by Yuqin Wu, Congqi Shen, Shungen Xiao, Wei Feng, Yexian Fan, Xiuzhuang Zhou

    Published 2025-05-01
    “…Moreover, we introduce a cross-model method with a genetic algorithm to compute the optimal weights for the RBF-NN model. …”
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    Article
  8. 1088

    Optimizing Non-Terrestrial Hybrid RF/FSO Links With Reinforcement Learning: Navigating Through Clouds by Abdullateef Almohamad, Mostafa Ibrahim, Sabit Ekin, Mazen Hasna, Saud Althunibat, Khalid Qaraqe

    Published 2025-01-01
    “…This paper introduces a reinforcement learning-based algorithm designed to optimize the trajectory of HAPS, maneuver around cloudy areas, and seamlessly switch between the RF and FSO communication modes to maximize the achievable capacity. …”
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    Article
  9. 1089

    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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    Article
  10. 1090

    Optimal Configuration Method for Electric-thermo-hydrogen System Considering Safety Risks by Chouwei NI, Yang CHEN, Xuesong ZHANG, Da LIN, Kaijian DU, Jian CHEN

    Published 2024-09-01
    “…Furthermore, the safety risk coefficient is used to convert the safety risk of the hydrogen storage tank into the objective function. The optimal configuration model of the ETHS is then established with the system investment cost, operation cost, and safety risk as optimization objectives, and the tabu chaotic quantum particle swarm optimization (TCQPSO) algorithm is employed to solve the model. …”
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    Article
  11. 1091

    Fusing Algorithms for Intersection of Computer Science and Art: Innovations in Generative Art and Interactive Digital Installations by Jingpeng Xie, Miaomiao Yu, Guangliang Liu

    Published 2024-01-01
    “…The study focuses on how these advanced algorithms can enhance artistic expression and interactivity, providing novel approaches for generating and optimizing art. …”
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    Article
  12. 1092

    Maximum Torque per Ampere Control of PMSMs Using Real-Time Numerical Optimization by Yong Xu, Min-Yi Lin, Wen-Jie Wan, Yunchong Wang, Jian-Xin Shen

    Published 2025-01-01
    “…It is evaluated alongside the Levenberg-Marquardt algorithm (LMA), which is renowned for its high accuracy and rapid convergence. …”
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    Article
  13. 1093

    Fractional Order PID Controller Based‐Neural Network Algorithm for LFC in Multi‐Area Power Systems by Ali M. El‐Rifaie, Slim Abid, Ahmed R. Ginidi, Abdullah M. Shaheen

    Published 2025-02-01
    “…The proposed method demonstrates marked improvements over traditional PID controllers and advanced optimization techniques such as Differential Evolution (DE) and Artificial Rabbits Algorithm (ARA). …”
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    Article
  14. 1094

    Risk management strategies for fuel shortages in economic dispatch with multiple fuel options using walrus algorithm by Mahmoud Ibrahim Mohamed, Ali M. Yousef, Ahmed A. Hafez

    Published 2025-09-01
    “…This article comprehensively analyzes the ED process for power plants with multiple fuel options, while achieving multiple objectives: optimizing energy management and boosting supply security. …”
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  15. 1095
  16. 1096

    Optimizing Route Planning via the Weighted Sum Method and Multi-Criteria Decision-Making by Guanquan Zhu, Minyi Ye, Xinqi Yu, Junhao Liu, Mingju Wang, Zihang Luo, Haomin Liang, Yubin Zhong

    Published 2025-05-01
    “…Secondly, this study compares seven heuristic algorithms—the genetic algorithm (GA), particle swarm optimization (PSO), the tabu search (TS), genetic-particle swarm optimization (GA-PSO), the gray wolf optimizer (GWO), and ant colony optimization (ACO)—to solve the TOPSIS model, with GA-PSO performing the best. …”
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    Article
  17. 1097

    Leveraging Game Theory to Design Incentive-Compatible Time-Varying electricity pricing with Demand-Side management by Magda I. El-Afifi, Bishoy E. Sedhom, Abdelfattah A. Eladl, Padmanaban Sanjeevikumar, Samaa Fawzy

    Published 2024-10-01
    “…To address this, the influence of two optimization algorithms, Genetic Algorithm (GA) and Archimedes Optimization Algorithm (AOA), on user electricity bills and peak-to-average ratio following load scheduling is examined. …”
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    Article
  18. 1098

    A configuration and scheduling optimization method for integrated energy systems considering massive flexible load resources by Zihao Wang, Shenhua Wang, Hanwen Ni, Junyin Wang, Jun Zhang

    Published 2025-03-01
    “…The EKOA algorithm significantly reduced curtailment rates of wind and solar power generation while achieving substantial economic benefits. …”
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  19. 1099

    Simultaneous Energy Optimization of Heating Systems by Multi-Zone Predictive Control—Application to a Residential Building by Rina Bitar, Nicolas Youssef, Julien Chamoin, Fadi Hage Chehade, Didier Defer

    Published 2024-10-01
    “…The research methodology uses dynamic thermal simulation, parallel predictive models based on multiple linear regressions, and a multi-objective non-dominated sorting genetic algorithm II (NSGA-II) for the optimization process, which evaluates various generated heating strategies. …”
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  20. 1100

    A genetic algorithm-based solution for multi-type maximal covering location problem (MMCLP): application to defense and deterrence by J.D. Lessan, Geoff Pond

    Published 2024-12-01
    “…Design/methodology/approach – In our case study, we use open source geographic and demographic data from Canadian sources as inputs to our optimization problem. Due to the complexity of the MIP formulation, we propose a hybrid metaheuristic solution approach, for which a genetic algorithm (GA) is proposed and integrated with local and large neighborhood search operators. …”
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