Multi-Strategy Improvement of Dun Beetle Optimizer

A multi-strategy improved Dun Beetle Optimizer (MSIDBO) is proposed by this paper to address low convergence accuracy, weak global exploration capability, and susceptibility to local optima in the standard DBO. The MSIDBO algorithm improves DBO by incorporating dual Levy flight random numbers, adaptive adjustment, and probability perturbation strategies, which effectively balances the development and exploration of the optimization algorithm and enhances its optimization performance. Apart from its evaluation on 12 benchmark test functions, this algorithm is compared with various efficient optimization algorithms, demonstrating superior optimization performance compared to the selected benchmark algorithms and providing valuable references for practical engineering applications.