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Chaotic-based BVM algorithm for solving optimization and engineering problems
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DOI：10.1080/02286203.2026.2691877.png)
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Abstract
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This paper introduces a novel Chaotic-Based BVM (CBVM) algorithm, a meta-heuristic optimization approach inspired by the Hindu Trimurti-Lord Brahma, Vishnu, and Mahesh. Reflecting their divine roles, the algorithm consists of three phases: population generation (Brahma), position updating to preserve diversity (Vishnu), and elimination of inferior solutions (Mahesh). To enhance the balance between exploration and exploitation, CBVM incorporates chaotic maps, improving search efficiency, population diversity, and convergence speed while reducing the risk of premature convergence. The performance of CBVM is evaluated on the CEC2005 and CEC2019 benchmark suites and statistically validated using t-test, Friedman test, and Wilcoxon rank-sum test. Experimental results demonstrate that CBVM consistently outperforms several existing algorithms by effectively avoiding local optima and achieving superior global convergence. Furthermore, its successful application to real-world engineering design problems highlights its robustness, adaptability, and effectiveness in solving both constrained and unconstrained optimization problems.
Keywords:
Optimization
meta-heuristic algorithms
chaotic maps
engineering applications
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