An integrative TLBO-driven hybrid grey wolf optimizer for the efficient resolution of multi-dimensional, nonlinear engineering problems

An integrative TLBO-driven hybrid grey wolf optimizer for the efficient resolution of multi-dimensional, nonlinear engineering problems

Abstract This research article introduces a hybrid optimization algorithm, referred to as Grey Wolf Optimizer-Teaching Learning Based Optimization (GWO-TLBO), which extends the Grey Wolf Optimizer (GWO) by integrating it with Teaching-Learning-Based Optimization (TLBO). The benefit of GWO is that it...

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Bibliographic Details
Main Authors: Harleenpal Singh, Sobhit Saxena, Himanshu Sharma, Vikram Kumar Kamboj, Krishan Arora, Gyanendra Prasad Joshi, Woong Cho
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Performance benchmarks
Population-based metaheuristics
Global optimization
Engineering design challenges
Computational algorithms
Optimization techniques
Online Access:https://doi.org/10.1038/s41598-025-89458-3
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https://doi.org/10.1038/s41598-025-89458-3

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