Convergence properties of stochastic optimization procedures
- 1 January 1984
- journal article
- research article
- Published by Taylor & Francis in Mathematische Operationsforschung und Statistik. Series Optimization
- Vol. 15 (3) , 405-427
- https://doi.org/10.1080/02331938408842957
Abstract
General convergence characteristics of stochastic optimization methods are investigated, when convex and/or differentiable structure of the optimization problems to be solved is not assumed, First, some basic stochastic optimization schemes are introduced and their convergence properties are analysed, then the obtained results are extended for the case of stochastically combined (hybrid) procedures. Finally, some experimental results with hybrid optimization methods are summarized.Keywords
This publication has 8 references indexed in Scilit:
- Convergence of a random optimization method for constrained optimization problemsJournal of Optimization Theory and Applications, 1981
- Minimization by Random Search TechniquesMathematics of Operations Research, 1981
- Conjugate Direction Methods in OptimizationPublished by Springer Nature ,1980
- Progressive global random search of continuous functionsMathematical Programming, 1978
- Nonlinear programming methods in the presence of noiseMathematical Programming, 1978
- Stochastic Approximation Methods for Constrained and Unconstrained SystemsPublished by Springer Nature ,1978
- Contributions to the theory of stochastic programmingMathematical Programming, 1973
- Function minimization by conjugate gradientsThe Computer Journal, 1964