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

Authors:
Otis Brooks
Affiliations:
The Johns Hopkins University Applied Physics Laboratory, Laurel, MD
Venue:
SpringSim '07 Proceedings of the 2007 spring simulation multiconference - Volume 3
Year:
2007

Citing 2
Cited 1

Optimization over discrete sets via SPSA

Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Introduction to Stochastic Search and Optimization

Introduction to Stochastic Search and Optimization

A study of the analytical method for the location planning of charging stations for electric vehicles

KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part III

Quantified Score

Hi-index	0.00

Visualization

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.