Generating Random Deviates Consistent with the Long Term Behavior of Stochastic Search Processes in Global Optimization
A new stochastic search algorithm is proposed, which in first instance is capable to give a probability density from which populations of points that are consistent with the global properties of the associated optimization problem can be drawn. The procedure is based on the Fokker – Planck equation, which is a linear differential equation for the density. The algorithm is constructed in such a way that only involves linear operations and a relatively small number of evaluations of the given cost function.
Keywordsglobal optimization stochastic search statistical physics
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