An Asymptotic Test of Optimality Conditions in Multiresponse Simulation Optimization

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Angun E., Kleijnen J.

INFORMS JOURNAL ON COMPUTING, vol.24, no.1, pp.53-65, 2012 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 24 Issue: 1
  • Publication Date: 2012
  • Doi Number: 10.1287/ijoc.1100.0438
  • Journal Name: INFORMS JOURNAL ON COMPUTING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.53-65
  • Keywords: simulation, design of experiments, simulation, statistical analysis, black-box simulation-optimization, white-box simulation-optimization, SYSTEMS
  • Galatasaray University Affiliated: Yes

Abstract

This paper derives a novel, asymptotic statistical test of the Karush-Kuhn-Tucker first-order necessary optimality conditions in random simulation models with multiple responses. This test combines a simple form of the delta method and a generalized version of Wald's statistic. The test is applied to both a toy problem and an (s, S) inventory-optimization problem with a service-level constraint; its numerical results are encouraging.