Solution of stochastic multi-objective system reliability design problems using genetic algorithms

David W. Coit, Fatema Baheranwala

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

A methodology is presented to solve multiple-objective system reliability design problems with some (or all) stochastic objectives. For these problems, the objective is to determine the maximum system reliability, but at a minimum cost and weight without explicit constraint limits. The reliability and cost objectives are not known exactly due to estimation uncertainties and cost fluctuations, respectively. Objective function variance measures are explicitly included in the formulation as additional objectives to be minimized for riskaverse decision makers. A multi-objective genetic algorithm is used to initially find Pareto optimal solutions, which are then prioritized based on the decision makers objective function preferences. The methodology is demonstrated on several test problems.

Original languageEnglish (US)
Title of host publicationAdvances in Safety and Reliability - Proceedings of the European Safety and Reliability Conference, ESREL 2005
Pages391-398
Number of pages8
StatePublished - 2005
Event16th European Safety and Reliability Conference, ESREL 2005 - Tri City, Poland
Duration: Jun 27 2005Jun 30 2005

Publication series

NameAdvances in Safety and Reliability - Proceedings of the European Safety and Reliability Conference, ESREL 2005
Volume1

Other

Other16th European Safety and Reliability Conference, ESREL 2005
Country/TerritoryPoland
CityTri City
Period6/27/056/30/05

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality

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