Sequential approximate optimization using variable fidelity response surface approximations

2000 ◽  
Author(s):  
Jose Rodriguez ◽  
Victor Perez ◽  
John Renaud
Keyword(s):  
Response Surface ◽  
Sequential Approximate Optimization ◽  
Approximate Optimization ◽  
Response Surface Approximations ◽  
Variable Fidelity

Decoupling the Design Sampling Region From the Trust Region in Approximate Optimization

2000 ◽  
Author(s):  
Victor M. Pérez ◽  
John E. Renaud
Keyword(s):  
Convergence Rate ◽  
Response Surface ◽  
Design Space ◽  
Trust Region ◽  
Good Representation ◽  
Approximate Representation ◽  
Design Problems ◽  
Computational Costs ◽  
Approximate Optimization ◽  
Response Surface Approximations

Abstract Response Surface Approximations (RSA’s) are widely used in the design community to provide designers with an approximate representation of a system. The use of RSA’s allow designers to query the system while avoiding the high computational costs associated with today’s advanced simulation codes. Sequential Approximate Optimization (SAO) methodologies have proved to be effective in managing the optimization of multi-disciplinary design problems. In SAO the sampling required to build the RSA’s often takes place within the same bounds as imposed on the current optimization iterate. This assures a good representation of the system in the region where it will be optimized. However it may restrict the approximation from extrapolating beyond the design space, and therefore improve the convergence rate of the algorithm. In this research a decoupling of the sampling region from the trust region is proposed.

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