Title :
An optimization algorithm driven by probabilistic simulation
Author :
Maheshwari, S. ; Mukai, H.
Author_Institution :
Washington University, St.Louis, MO
Abstract :
In this short paper we present an algorithm for optimization problems in which the evaluation of the objective function and of its gradient requires Monte Carlo-type probabilistic simulation. The algorithm is based on the gradient method and the paper also presents its convergence analysis.
Keywords :
Algorithm design and analysis; Analytical models; Approximation methods; Convergence; Cost function; Gradient methods; Network servers; Optimization methods; Space stations; Stochastic processes;
Conference_Titel :
Decision and Control, 1986 25th IEEE Conference on
Conference_Location :
Athens, Greece
DOI :
10.1109/CDC.1986.267226
