Solving discrete resource allocation problems using the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm

Abstract

We investigate optimization techniques for solving a class of discrete resource allocation problems, including several discrete forms of Simultaneous Perturbation Stochastic Optimization (SPSA). We explore the rate-of-convergence for discrete SPSA in a stochastic setting. Finally, we consider some of the difficulties that can arise when discrete resource allocation problems include a stochastic component.