Title :
A stochastic optimization algorithm based on Newton-type method
Author :
Maheshwari, Sandeep
Author_Institution :
Dept. of Math., William Paterson Coll., Wayne, NJ, USA
Abstract :
An algorithm is presented for optimization problems in which the objective function, its gradient, and its Hessian would require Monte-Carlo-type simulations. First, a conceptual algorithm is presented. Then, an implementable version of this conceptual algorithm, based on the idea of Newton´s method, is given, together with convergence results and the conditions needed to achieve convergence
Keywords :
convergence of numerical methods; iterative methods; large-scale systems; stochastic programming; Hessian; Monte-Carlo-type simulations; Newton-type method; convergence conditions; large-scale systems; objective function; stochastic optimization algorithm; Assembly systems; Convergence; Cost function; Discrete event systems; Educational institutions; Mathematics; Newton method; Optimization methods; Stochastic processes; Transportation;
Conference_Titel :
Decision and Control, 1989., Proceedings of the 28th IEEE Conference on
Conference_Location :
Tampa, FL
DOI :
10.1109/CDC.1989.70253
