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arXiv · cond-mat/9501047

Generalized Simulated Annealing

Constantino Tsallis·Daniel A. Stariolo
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Abstract

We propose a new stochastic algorithm (generalized simulated annealing) for computationally finding the global minimum of a given (not necessarily convex) energy/cost function defined in a continuous D-dimensional space. This algorithm recovers, as particular cases, the so called classical ("Boltzmann machine") and fast ("Cauchy machine") simulated annealings, and can be quicker than both. Key-words: simulated annealing; nonconvex optimization; gradient descent; generalized statistical mechanics.

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Constantino Tsallis, Daniel A. Stariolo. 1995-01-12. Generalized Simulated Annealing. https://doi.org/10.1016/s0378-4371(96)00271-3

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