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SPSA algorithm for fuzzy random time inspection policy

  • Song Xu*
  • , Zhong Feng Qin
  • , Xia Zhang
  • *Corresponding author for this work
  • Tianjin University
  • Tsinghua University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The time inspection policy is one of the most common maintenance policies. In this paper, a time inspection policy is studied in which the lifetimes of components are treated as fuzzy random variables. The concept of the long-run expected cost per unit time is put forward. In order to minimize the long- run expected cost per unit time, a fuzzy random expected value model is established. The fuzzy random simulation technique is employed to estimate the value of the objective function and the simultaneous perturbation stochastic approximation (SPSA) algorithm is employed to search the optimal solution. Finally, a numerical example is presented to illustrate the effectiveness of the algorithm.

Original languageEnglish
Title of host publication2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005
PublisherIEEE Computer Society
Pages2628-2633
Number of pages6
ISBN (Electronic)0780390911
ISBN (Print)078039092X, 9780780390928
DOIs
StatePublished - 2005
Externally publishedYes
EventInternational Conference on Machine Learning and Cybernetics, ICMLC 2005 - Guangzhou, China
Duration: 18 Aug 200521 Aug 2005

Publication series

Name2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005
Volume5

Conference

ConferenceInternational Conference on Machine Learning and Cybernetics, ICMLC 2005
Country/TerritoryChina
CityGuangzhou
Period18/08/0521/08/05

Keywords

  • Fuzzy random simulation
  • Fuzzy random variable
  • Fuzzy variable
  • Maintenance policy
  • SPSA algorithm

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