29 October 1993 Fast stochastic global optimization
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Abstract
A new stochastic optimization algorithm is introduced in which a pipeline of many biased stochastic procedures cooperate to concurrently sample the usual Boltzmann distribution for different temperatures. Convergence and efficiency of the pipeline algorithm is proved under certain conditions. Experimental confirmation is provided using seven standard test problems in nonlinear optimization.
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Griff L. Bilbro, "Fast stochastic global optimization", Proc. SPIE 2032, Neural and Stochastic Methods in Image and Signal Processing II, (29 October 1993); doi: 10.1117/12.162050; https://doi.org/10.1117/12.162050
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