Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Statistics
  • Help & Advice
University of Warwick

The Library

  • Login

Reliability-based optimization using evolutionary algorithms

Tools
- Tools
+ Tools

Deb, Kalyanmoy, Gupta, Shubham, Daum, David, Branke, Jürgen, 1969-, Mall, Abhishek Kumar and Padmanabhan, Dhanesh. (2009) Reliability-based optimization using evolutionary algorithms. IEEE Transactions on Evolutionary Computation, Vol.13 (No.5). pp. 1054-1074. ISSN 1089-778X

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1109/TEVC.2009.2014361

Abstract

Uncertainties in design variables and problem parameters are often inevitable and must be considered in an optimization task if reliable optimal solutions are sought. Besides a number of sampling techniques, there exist several mathematical approximations of a solution's reliability. These techniques are coupled in various ways with optimization in the classical reliability-based optimization field. This paper demonstrates how classical reliability-based concepts can be borrowed and modified and, with integrated single and multiobjective evolutionary algorithms, used to enhance their scope in handling uncertainties involved among decision variables and problem parameters. Three different optimization tasks are discussed in which classical reliability-based optimization procedures usually have difficulties, namely 1) reliability-based optimization problems having multiple local optima, 2) finding and revealing reliable solutions for different reliability indices simultaneously by means of a bi-criterion optimization approach, and 3) multiobjective optimization with uncertainty and specified system or component reliability values. Each of these optimization tasks is illustrated by solving a number of test problems and a well-studied automobile design problem. Results are also compared with a classical reliability-based methodology.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Divisions: Faculty of Social Sciences > Warwick Business School
Journal or Publication Title: IEEE Transactions on Evolutionary Computation
Publisher: IEEE
ISSN: 1089-778X
Date: October 2009
Volume: Vol.13
Number: No.5
Number of Pages: 21
Page Range: pp. 1054-1074
Identification Number: 10.1109/TEVC.2009.2014361
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Funder: Foundation of Helsinki School of Economics
Grant number: 118319
URI: http://wrap.warwick.ac.uk/id/eprint/17262

Data sourced from Thomson Reuters' Web of Knowledge

Request changes to a record

Actions (login required)

View Item View Item
twitter

Email us: publications@warwick.ac.uk
Contact Details
About Us