Abstract
During the past two years a great deal of attention has been given to simulated annealing as a global minimization algorithm in combinatorial optimization problems [11], image processing problems [2], and other problems [9]. The first rigorous result concerning the convergence of the annealing algorithm was obtained in [2]. In [4], the annealing algorithm was treated as a special case of non-stationary Markov chains, and some optimal convergence estimates and an ergodic theorem were established. Optimal estimates for the annealing algorithm have recently been obtained by nice intuitive arguments in [7].
Partially supported by NSF Grant MCS-8301864.
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© 1986 Springer-Verlag Berlin Heidelberg
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Gidas, B. (1986). The Langevin Equation as a Global Minimization Algorithm. In: Bienenstock, E., Soulié, F.F., Weisbuch, G. (eds) Disordered Systems and Biological Organization. NATO ASI Series, vol 20. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-82657-3_31
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DOI: https://doi.org/10.1007/978-3-642-82657-3_31
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