Multi Points Updated and Distance Filtered Kriging Surrogate Model: Application in EOSS Optimization

LIU Xiaolu; CHEN Yingwu; CHEN Yingguo; HE Renjie

Article Contents

Article Navigation > Chinese Journal of Electronics > 2013 > 22(1): 209-213

LIU Xiaolu, CHEN Yingwu, CHEN Yingguo, HE Renjie. Multi Points Updated and Distance Filtered Kriging Surrogate Model: Application in EOSS Optimization[J]. Chinese Journal of Electronics, 2013, 22(1): 209-213.

Citation:

LIU Xiaolu, CHEN Yingwu, CHEN Yingguo, HE Renjie. Multi Points Updated and Distance Filtered Kriging Surrogate Model: Application in EOSS Optimization[J]. Chinese Journal of Electronics, 2013, 22(1): 209-213.

Citation:

PDF( 241 KB)

Multi Points Updated and Distance Filtered Kriging Surrogate Model: Application in EOSS Optimization

School of Information System and Management, National University of Defense Technology, Changsha 410073, China

Funds: This work is supported by the National Natural Science Foundation of China (No.70171156, No.70971131).

Received Date: 2011-11-01
Rev Recd Date: 2012-04-01
Publish Date: 2013-01-05

Abstract

Abstract

We put forward a multi points updated and distance filtered Kriging surrogate model. When building Kriging models, two update approaches are used to select infilling points: optimal points and maximized expected improvement. We use Improved general pattern search (IGPS) algorithm to get these points. In IGPS, search step is substituted by GA and SQP and poll step is retained. To decrease simulation times, we adopt a distance filter to eliminate potentially replicated samples. A satellite orbit parameter optimization problem is formulated, which is solved by the proposed method and STK/Analyzer respectively. The results showed that Kriging models, which use multi update points and distance filter, yield global approximations that are more accurate than Analyzer.

FullText(HTML)

References(16)

References

J.P.C. Kleijnen, “Kriging metamodeling in simulation: A review”,European Journal of Operational Research, Vol.192,No.3, pp.707-716, 2007.

V.R. Joseph, Y. Hung and A. Sudjianto, “Blind kriging: A newmethod for developing metamodels”, J. Mech. Des, Vol.130,No.3, pp.1-8, 2008.

D.W. Apley, J.L. Lin and W. Chen, “Understanding the effectsof model uncertainty in robust design with computer experiments”,ASME J. Mech. Des, Vol.128, No.4, pp.945-958, 2006.

T.W. Simpson, T.M. Mauery, J.J. Korte and F. Mistree,“Kriging Models for global approximation in simulation-basedmultidisciplinary design optimization”, AIAA Journal, Vol.39,No.12, pp.2233-2241, 2001.

N.V. Queipoa, R.T. Haftkaa, W. Shyya et al., “Surrogate-basedanalysis and optimization”, Progress in Aerospace Sciences,Vol.41, No.1, pp.1-28, 2005.

Zhangjun Huang, Chengen Wang, Jian Chen and H. Tian, “Optimaldesign of aeroengine turbine disc based on kriging surrogatemodels”, Computers and Structures, Vol.89, No.1-2, pp.27-37, 2011.

G. Matheron, “Principles of geostatistics”, Economic Geology,Vol.58, No.8, pp.1246-1266, 1963.

E. Vazquez and JulienBect, “Convergence properties of theexpected improvement algorithm with fixed mean and covariancefunctions”, Journal of Statistical Planning and Inference,Vol.140, No.11, pp.3088-3095, 2010.

M.J. Sasena, “Flexibility and efficiency enhancements for constrainedglobal design optimization with kriging approximations”,Ph.D. Thesis, University of Michigan, USA, 2002.

V. Torczon, “On the convergence of pattern search algorithm”,SIAM Journal of Optimization, Vol.7, No.1, pp.1-25, 1997.

R.M. Lewis, Torczon, “Pattern search algorithms for bound constrainedminimization”, SIAM Journal of Optimization, Vol.9,No.4, pp.1082-1099, 1999.

R.M. Lewis, Torczon, “Pattern search methods for linearly constrainedminimization”, SIAM Journal of Optimization, Vol.10,No.3, pp.917-941, 1999.

B.F. Valls V, Quintanilla S, “A hybrid genetic algorithm forthe resource constrained project scheduling problem”, EuropeanJournal of Operational Research, Vol.185, No.2, pp.495-508,2008.

P.T. Boggs and J.W. Tolle, “Sequential quadratic programming”,Acta Numerica, Vol.4, pp.1-51, 1995.

J.W.C. Todd A. Sriver, Mark A. Abramson, “Pattern searchranking and selection algorithms for mixed variable simulationbasedoptimization”, European Journal of Operational Research,Vol.198, No.3, pp.878-890, 2009.

J.F. Cordeau and G. Laporte, “Maximizing the value of an earthobservation satellite orbit”, Journal of the Operational ResearchSociety, Vol.56, No.8, pp.962-968, 2005.

Relative Articles

Supplements(0)

Cited By

Proportional views