Showing 1,081 - 1,100 results of 7,339 for search 'evolutionary three', query time: 0.11s Refine Results
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    Combining Parallel Stochastic Methods and Mixed Termination Rules in Optimization by Vasileios Charilogis, Ioannis G. Tsoulos, Anna Maria Gianni

    Published 2024-09-01
    “…In this study, a combination of termination criteria is proposed, utilizing three different criteria to end the algorithmic process. …”
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  13. 1093

    A New Bipolar Approach Based on the Rooster Algorithm Developed for Utilization in Optimization Problems by Mashar Cenk Gençal

    Published 2025-04-01
    “…Meta-heuristic algorithms are computational methods inspired by evolutionary processes, animal or plant behaviors, physical events, and other natural phenomena. …”
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  14. 1094

    An Evolutional Topology Optimization Method Based on Kernel Level Set Function by Takahiro Sato, Kota Watanabe, Hajime Igarashi

    Published 2025-01-01
    “…Topology optimizations involving evolutionary algorithms are promising approaches to solve practical engineering design problems, since their use of derivation-free algorithms makes them applicable to any design problem. …”
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  15. 1095

    Beamline Optimisation for High-Intensity Muon Beams at PSI Using the Heterogeneous Island Model by Eremey Valetov, Giovanni Dal Maso, Peter-Raymond Kettle, Andreas Knecht, Angela Papa

    Published 2024-08-01
    “…We are now developing an island-based evolutionary optimisation code <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi mathvariant="monospace">glyfada</mi></semantics></math></inline-formula> based on the Paradis<b>eo</b> framework, where we implemented Message Passing Interface (MPI) islands with OpenMP parallelisation within each island. …”
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  16. 1096

    Bio-Inspired Multiobjective Optimization for Designing Content Distribution Networks by Gerardo Goñi, Sergio Nesmachnow, Diego Rossit, Pedro Moreno-Bernal, Andrei Tchernykh

    Published 2025-04-01
    “…The obtained results represent an improvement over greedy heuristics from 47.6% to 93.3% in terms of cost while maintaining competitive quality of service. …”
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