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April 21, 2026Scientific ReportsOpen Access

Multi-strategy enhanced black-winged kite algorithm and its engineering applications

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Authors

MLMeijin LinZQZhirong QiuWZWeijia Zheng

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Overview

This algorithm enhances optimization performance, indicating improvements in engineering applications.

Key Points

  • The research aims to improve the Black-winged Kite Algorithm (BKA) by addressing its convergence issues in optimization problems.
  • Developed a Multi-strategy Enhanced Black-winged Kite Algorithm (MSEBKA) with four key strategies: adaptive inertia weight, elite pool, dynamic Gaussian random walk, and lens imaging opposition-based learning.
  • Conducted experiments on CEC2019 and CEC2021 benchmark functions to evaluate performance.
  • Applied the MSEBKA to five constrained optimization engineering problems.
  • MSEBKA outperformed the original BKA algorithm on 6 out of 10 CEC2019 benchmark functions regarding mean fitness and standard deviation.
  • Achieved superior Friedman mean ranks compared to BKA and other metaheuristic algorithms across multiple benchmarks.
  • Demonstrated better performance on five engineering design problems, with notable percentage improvements in design outcomes.

Cite This Study

Lin et al. (2026) studied this question.

synapsesocial.com/papers/69e7138bcb99343efc98cff8https://doi.org/10.1038/s41598-026-39736-5
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