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

Revision as of 15:25, 4 April 2013

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.