16 December 1992 Continuous-state simulated annealing algorithms: theory and application
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Abstract
Simulated annealing algorithms for optimization over continuous spaces come in two varieties: Markov chain algorithms and modified gradient algorithms. Unfortunately, there is a gap between the theory and the application of these algorithms: the convergence conditions cannot be practically implemented. In this paper we suggest a practical methodology for implementing the modified gradient annealing algorithms based on their relationship to the Markov chain algorithms.
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Saul B. Gelfand, Peter C. Doerschuk, Mohamed Nahhas-Mohandes, "Continuous-state simulated annealing algorithms: theory and application", Proc. SPIE 1766, Neural and Stochastic Methods in Image and Signal Processing, (16 December 1992); doi: 10.1117/12.130832; https://doi.org/10.1117/12.130832
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