Abstract
This algorithm for global optimization uses an arbitrary starting point, requires no derivatives, uses comparatively few function evaluations and is not side-tracked by nearby relative optima. The algorithm builds a gradually closer piecewise-differentiable approximation to the objective function. The computer program exhibits a (theoretically expected) strong tendency to cluster around relative optima close to the global. Results of testing with several standard functions are given.
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Mladineo, R.H. An algorithm for finding the global maximum of a multimodal, multivariate function. Mathematical Programming 34, 188–200 (1986). https://doi.org/10.1007/BF01580583
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DOI: https://doi.org/10.1007/BF01580583