Difference between revisions of "Adaptive simulated annealing (analysis)"

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:[[File:Optimization-Adaptive-simulated-annealing-icon.png]] Adaptive simulated annealing
 
:[[File:Optimization-Adaptive-simulated-annealing-icon.png]] Adaptive simulated annealing

Revision as of 16:16, 14 June 2013

Analysis title
Optimization-Adaptive-simulated-annealing-icon.png Adaptive simulated annealing
Provider
Institute of Systems Biology
Class
ASAOptMethod
Plugin
ru.biosoft.analysis.optimization (Common methods of data optimization analysis plug-in)

Adaptive simulated annealing (ASA)

ASA algorithm1 is developed to statistically find the best global fit of a nonlinear non-convex 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 = T0exp(-ck(1/D)). The introduction of re-annealing also permits adaptation to changing sensitivities in the multi-dimensional parameter-space. This annealing schedule is faster than fast Cauchy annealing, where T = T0/k, and much faster than Boltzmann annealing, where T = T0/ln k.

References

  1. L Ingber, "Adaptive simulated annealing (ASA): Lessons learned." Control and Cybernetics, Vol. 25, No. 1, pp. 33-54, 1996.
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