Very fast simulated re-annealing. (English) Zbl 0681.90091

Summary: An algorithm is developed to statistically find the best global fit of a nonlinear nonconvex cost-function over a D-dimensional space. It is argued that this algorithm permits an annealing schedule for “temperature” T decreasing exponentially in annealing-time k, \(T=T_ 0\exp (-ck^{1/D})\). The introduction of re-annealing also permits to changing insensitivities in the multidimensional parameter-space. This annealing schedule is faster than fast Cauchy annealing, where \(T=T_ 0/k\), and much faster than Boltzmann annealing, where \(T=T_ 0/\ln k\). Applications are being made to fit empirical data to Lagrangians representing nonlinear Gaussian-Markovian systems.


90C99 Mathematical programming
74A15 Thermodynamics in solid mechanics
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