Non-Convex Optimization

Harold H. Szu

doi:10.1117/12.976247

23 March 1986 Non-Convex Optimization

Harold H. Szu

Proceedings Volume 0698, Real-Time Signal Processing IX; (1986) https://doi.org/10.1117/12.976247
Event: 30th Annual Technical Symposium, 1986, San Diego, United States

Abstract

A stochastic search technique called simulated annealing can solve a class of problems termed non-convex optimization by seeking the lowest minimum of a multi-minima function. Simulated annealing is a generalized Monte Carlo technique with a continuously decreasing variance controlled by the temperature parameter.

Citation Download Citation

Harold H. Szu "Non-Convex Optimization", Proc. SPIE 0698, Real-Time Signal Processing IX, (23 March 1986); https://doi.org/10.1117/12.976247

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