Robust parameter design optimization of simulation experiments using stochastic perturbation methods

A. K. Miranda, E. Del Castillo

Research output: Contribution to journalArticle

7 Scopus citations


Stochastic perturbation methods can be applied to problems for which either the objective function is represented analytically, or the objective function is the result of a simulation experiment. The Simultaneous Perturbation Stochastic Approximation (SPSA) method has the advantage over similar methods of requiring only two measurements at each iteration of the search. This feature makes SPSA attractive for robust parameter design (RPD) problems where some factors affect the variance of the response(s) of interest. In this paper, the feasibility of SPSA as a RPD optimizer is presented, first when the objective function is known, and then when the objective function is estimated by means of a discrete-event simulation.

Original languageEnglish (US)
Pages (from-to)198-205
Number of pages8
JournalJournal of the Operational Research Society
Issue number1
StatePublished - Jan 2011


All Science Journal Classification (ASJC) codes

  • Management Information Systems
  • Strategy and Management
  • Management Science and Operations Research
  • Marketing

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