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Reliability-Based Optimization Using Evolutionary Algorithms

Author(s)
Deb, Kalyanmoy; Gupta, Shubham; Daum, David; Branke, Jurgen; Mall, Abhishek Kumar; Padmanabhan, Dhanesh; ... Show more Show less
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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.
Date issued
2009-09
URI
http://hdl.handle.net/1721.1/52374
Department
Massachusetts Institute of Technology. Operations Research Center
Journal
IEEE Transactions on Evolutionary Computation
Publisher
Institute of Electrical and Electronics Engineers
Citation
Deb, K. et al. “Reliability-Based Optimization Using Evolutionary Algorithms.” Evolutionary Computation, IEEE Transactions on 13.5 (2009): 1054-1074. © 2009 Institute of Electrical and Electronics Engineers
Version: Final published version
Other identifiers
INSPEC Accession Number: 10879800
ISSN
1089-778X
Keywords
system reliability, reliable front, reliability-based optimization, pareto-optimal front, most probable point, evolutionary multiobjective optimization, Ditlevsen's bound

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