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Page 1: Editorial Uncertainty-Based Design Optimization in ...Uncertainty-Based Design Optimization in Engineering: Model, Algorithm, and Application XiaojunWang, 1 ZhipingQiu, 1 andDirkSöffker

Hindawi Publishing CorporationJournal of Applied MathematicsVolume 2013, Article ID 595719, 2 pageshttp://dx.doi.org/10.1155/2013/595719

EditorialUncertainty-Based Design Optimization in Engineering:Model, Algorithm, and Application

Xiaojun Wang,1 Zhiping Qiu,1 and Dirk Söffker2

1 Institute of Solid Mechanics, Beihang University, Beijing 100191, China2Department of Mechanical Engineering, University of Duisburg-Essen, 47048 Duisburg, Germany

Correspondence should be addressed to Zhiping Qiu; [email protected]

Received 25 September 2013; Accepted 25 September 2013

Copyright © 2013 Xiaojun Wang et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Uncertainty widely exists in inherent characteristics or exter-nal environment of practical engineering problems.The com-prehensive influence of uncertainty on products has alreadybeen one of themost significant evaluation criterions to betterguide the subsequent R&D design. Thus, the uncertainty-based design optimization (UBDO) will become an inex-orable trend and main attention in the fields of academicstudy and engineering applications.

Three parts should be emphasized particularly inUBDOE. The first is the construction of uncertain analyticalmodel, that is, to estimate/quantify uncertainty and furthermake it embody in the objective function or constraint con-dition of optimal process. Next in importance is the develop-ment of algorithm. Efficiency, convergence and stability areall needed to take account of. The third is the combination ofthe theoretical approaches and practical problems, namely,to formulate mathematical system reasonably from trueenvironment. This issue complies 17 existing papers, most ofwhich are commendably performed with reference to one ofthe above 3 aspects.

Four of the papers deal with the first aspect in greatdepth. S. Seker et al. proposed a weighted multiobjectiveoptimization method for mixed-model assembly line prob-lem based on a mixed integer programming technique. A.Saavedra et al. established a generalized linear spatial model(GLSM) to explore relationship between exploitability anddifferent explanatory variables that characterize slate qual-ity. A time-dependent reliability-based design optimization(RBDO) method by Y. Wang et al. was developed to consider

both the time-dependent kinematic reliability and the time-dependent structural reliability as constrains. In this study, anonintrusive time-dependent surrogate model derived frompolynomial chaos with the moving least squares (PCMLS)was proposed to achieve uncertainty quantification. Further-more, the paper authored by Y. Lei et al. presented a proba-bilistic approach for the identification of structural damageand unknown external excitations using only limited mea-surements of structural acceleration responses contaminatedby intensive measurement noises.

The research on the second algorithm is addressed on twopapers, one of which by P. Tontragunrat and S. Bureerat inves-tigated ametaheuristicmethod by virtue of population-basedincremental learning (PBIL) to solve the anti-optimizationproblem subjected to the truss structure. Another one iscontributed by Y. Li and C.-L. Zheng who launched an inves-tigation in the complex network synchronization via chaoscontrol nodes. They adopted different order chaotic systemsas the nodes for complex network with the help of symboliccomputation, and the structure of coupling functions amongthe connected nodes was obtained based on Lyapunov stabil-ity theory.

In the aspect of engineering application, a fuzzy multi-objective design model used to minimize the length of trafficqueue and pedestrian delays is proposed by N. S. Pouret al., who also introduced the genetic algorithm and a newdefuzzification method. Treatments in other fields, includingby principal component pursuit (PCP) as well as estimationof stock return are, respectively, studied byQ. You andG.Cao.

Page 2: Editorial Uncertainty-Based Design Optimization in ...Uncertainty-Based Design Optimization in Engineering: Model, Algorithm, and Application XiaojunWang, 1 ZhipingQiu, 1 andDirkSöffker

2 Journal of Applied Mathematics

We sincerely hope that our efforts by compiling thesepapers can enrich our readers and inspire researchers withregard to the seemingly common but actually important issueof UBDOE.

Xiaojun WangZhiping QiuDirk Soffker

Page 3: Editorial Uncertainty-Based Design Optimization in ...Uncertainty-Based Design Optimization in Engineering: Model, Algorithm, and Application XiaojunWang, 1 ZhipingQiu, 1 andDirkSöffker

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