Adaptive search with stochastic acceptance probabilities for global optimization

Authors:
Archis Ghate;Robert L. Smith
Affiliations:
Industrial Engineering, University of Washington, Box 352650, Seattle, WA 98195, USA;Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI 48109, USA
Venue:
Operations Research Letters
Year:
2008

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Abstract

We present an extension of continuous domain Simulated Annealing. Our algorithm employs a globally reaching candidate generator, adaptive stochastic acceptance probabilities, and converges in probability to the optimal value. An application to simulation-optimization problems with asymptotically diminishing errors is presented. Numerical results on a noisy protein-folding problem are included.