Skip navigation
Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/5338
Full metadata record
DC FieldValueLanguage
dc.contributor.authorChakraborty S.-
dc.contributor.authorChatterjee T.-
dc.contributor.authorChowdhury, Rajib-
dc.contributor.authorAdhikari S.-
dc.date.accessioned2020-10-06T14:54:10Z-
dc.date.available2020-10-06T14:54:10Z-
dc.date.issued2017-
dc.identifier.citationApplied Mathematical Modelling(2017), 47(): 726-744-
dc.identifier.issn0307904X-
dc.identifier.urihttps://doi.org/10.1016/j.apm.2017.03.040-
dc.identifier.urihttp://repository.iitr.ac.in/handle/123456789/5338-
dc.description.abstractRobust design optimization (RDO) is a field of optimization in which certain measure of robustness is sought against uncertainty. Unlike conventional optimization, the number of function evaluations in RDO is significantly more which often renders it time consuming and computationally cumbersome. This paper presents two new methods for solving the RDO problems. The proposed methods couple differential evolution algorithm (DEA) with polynomial correlated function expansion (PCFE). While DEA is utilized for solving the optimization problem, PCFE is utilized for calculating the statistical moments. Three examples have been presented to illustrate the performance of the proposed approaches. Results obtained indicate that the proposed approaches provide accurate and computationally efficient estimates of the RDO problems. Moreover, the proposed approaches outperforms popular RDO techniques such as tensor product quadrature, Taylor's series and Kriging. Finally, the proposed approaches have been utilized for robust hydroelectric flow optimization, demonstrating its capability in solving large scale problems. © 2017 Elsevier Inc.-
dc.language.isoen_US-
dc.publisherElsevier Inc.-
dc.relation.ispartofApplied Mathematical Modelling-
dc.subjectDifferential evolution algorithm-
dc.subjectPolynomial correlated function expansion-
dc.subjectRobust design optimization-
dc.subjectStochastic computation-
dc.titleA surrogate based multi-fidelity approach for robust design optimization-
dc.typeArticle-
dc.scopusid56242780800-
dc.scopusid56226100500-
dc.scopusid10046255200-
dc.scopusid24436440900-
dc.affiliationChakraborty, S., Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee, India-
dc.affiliationChatterjee, T., Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee, India-
dc.affiliationChowdhury, R., Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee, India-
dc.affiliationAdhikari, S., College of Engineering, Swansea University, Singleton Park, Swansea, SA2 8PP, United Kingdom-
dc.description.fundingSC and RC acknowledges the support of CSIR via grant no. 22(0712)/16/EMR-II. TC acknowledges the support of MHRD, Government of India.-
dc.description.correspondingauthorChakraborty, S.; Department of Civil Engineering, Indian Institute of Technology RoorkeeIndia; email: csouvik41@gmail.com-
Appears in Collections:Journal Publications [CE]

Files in This Item:
There are no files associated with this item.
Show simple item record


Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.