Approximation of the distribution of convergence times for stochastic global optimisation
Journal of Global Optimization
Large Derivations, Evolutionary Computation and Comparisons of Algorithms
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
Simulated annealing with asymptotic convergence for nonlinear constrained optimization
Journal of Global Optimization
Mathematical and Computer Modelling: An International Journal
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The behavior of simulated annealing algorithms is tightly related to the hierarchical decomposition of their configuration spaces in cycles. In the generalized annealing framework, this decomposition is defined recursively. In this paper, its structure is extensively studied, and it is shown that the decomposition can be achieved through an implementable algorithm which allows exact computation of the fundamental constants underlying the behavior of these algorithms.