Fast simulated annealing in R-d with an application to maximum likelihood estimation in state-space models
We study simulated annealing algorithms to maximise a function psi on a subset of R-d. In classical simulated annealing, given a current state theta(n) in stage n of the algorithm, the probability to accept a proposed state z at which psi is smaller, is exp(-beta(n+1)(psi(z) - psi (theta(n))) where (beta(n)) is the inverse temperature. With the standard logarithmic increase of (beta(n)) the probab
