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    Integrated transportation system planning with gravitational search algorithm approach based on fuzzy mutant controller by Alireza Hosseinzadeh Kashani, Seyed Ahmad Shayannia, Mohammad Mehdi Movahedi, Soheila Sardar

    Published 2025-03-01
    “…In these relations, <strong>3r </strong>is a uniform random variable in the interval [1,0], which is used to create the random property of the speed of the particle population optimization algorithm and the acceleration of the gravitational search algorithm in the gravitational particle population algorithm, and <strong>3C </strong>and <strong>4C</strong> are two constants to determine the degree of the speed of the particle population optimizer algorithm and the acceleration of the gravitational search algorithm in the gravitational particle population algorithm the values of which are considered 3C and 4C. …”
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    TS-SSA: An improved two-stage sparrow search algorithm for large-scale many-objective optimization problems. by Xiaozhi Du, Kai Chen, Hongyuan Du, Zongbin Qiao

    Published 2025-01-01
    “…In the first stage of TS-SSA, this paper proposes a many-objective sparrow search algorithm (MaOSSA) to mainly manages the convergence through the adaptive population dividing strategy and the random bootstrap search strategy. …”
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    Securing IoT Communications via Anomaly Traffic Detection: Synergy of Genetic Algorithm and Ensemble Method by Behnam Seyedi, Octavian Postolache

    Published 2025-06-01
    “…The second phase focuses on optimal feature selection using a Genetic Algorithm enhanced with eagle-inspired search strategies. …”
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    Research on vehicle scheduling for forest fires in the northern Greater Khingan Mountains by Jie Zhang, Junnan He, Shihao Ren, Pei Zhou, Jun Guo, Mingyue Song

    Published 2025-01-01
    “…Improvement of ordinary genetic algorithm, design of double population strategy selection operation, the introduction of chaotic search initialization population, to improve the algorithm’s solution efficiency and accuracy, through the northern pristine forest area of Daxing’anling real forest fire cases and generation of large-scale random fire point simulation experimental test to verify the effectiveness of the algorithm, to ensure that the effectiveness and reasonableness of the solution to the problem of forest fire emergency rescue vehicle scheduling program. …”
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    An RFCSO-based grid stability enhancement by integrating solar photovoltaic systems with multilevel unified power flow controllers by Swetha Monica Indukuri, Alok Kumar Singh, D. Vijaya Kumar

    Published 2024-12-01
    “…Furthermore, the ML-UPFC, controlled by a random forest cuckoo search optimization algorithm, enhances the fault ride-through capabilities and power regulation. …”
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    Routing algorithm for heterogeneous computing force requests based on computing first network by ZHANG Gang, LI Xi

    Published 2025-02-01
    “…An optimized genetic algorithm to address this issue was proposed. This algorithm was designed from both local and global perspectives: to ensure fast convergence to the target solution locally, a single parameter satisfying the randomness strategy was used to initialize the population, making it widely dispersed in the solution space; adopting a multi-parameter solution (or path) balanced selection strategy for selection operations, making the selected population rich and diverse; adopting a two-layer crossover strategy for crossover operations, with the aim of expanding the breadth of global search; adopting a multi parameter random single point mutation strategy for mutation operations, with the aim of deepening local search capabilities. …”
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    Structural Parameter Identification Using Multi-Objective Modified Directional Bat Algorithm by LIU Li-jun, LIN Ying-hai, SU Yong-hui, LEI Ying

    Published 2025-01-01
    “…MOMDBA addressed these limitations through three key improvements: 1) Individual Historical Best Position Tracking: This feature allowed the algorithm to retain and utilize the best individual solutions encountered during the search process, improving its ability to explore the solution space effectively. 2) Hybrid Global-Local Search Strategy: By combining global exploration with local exploitation, MOMDBA enhanced its ability to converge towards optimal solutions while avoiding local optima. 3) Elimination Mechanism: To maintain population diversity and prevent stagnation, low-performing individuals were periodically replaced with new solutions. …”
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