Reliability-based optimization using evolutionary algorithms
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 1089-778XFull text not available from this repository.
Official URL: http://dx.doi.org/10.1109/TEVC.2009.2014361
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|
|Number of Pages:||21|
|Page Range:||pp. 1054-1074|
|Access rights to Published version:||Restricted or Subscription Access|
|Funder:||Foundation of Helsinki School of Economics|
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