Parameter Sensitivity Analysis in Two-Level Design Optimization

1990 ◽  
Vol 112 (3) ◽  
pp. 354-361 ◽  
Author(s):  
W.-C. Li ◽  
S. Azarm

Parameter sensitivity analysis of a two-level design optimization problem can be decomposed into two levels. In the first-level, the sensitivities of the subproblems are calculated separately. In the second-level, the sensitivities obtained for the first-level subproblems are coordinated to obtain the overall sensitivity information. Using this approach, we cannot only obtain the overall effect that a small change in a parameter has on the optimum solution of a problem (or system) but also its local effects on the subproblems (or subsystems). A simple two-bar truss example demonstrates the approach.

Author(s):  
W.-C. Li ◽  
S. Azarm

Abstract Parameter sensitivity analysis of a two-level design optimization problem can be decomposed into two levels. In the first-level, the sensitivities of the subproblems are calculated separately. In the second-level, the sensitivities obtained for the first-level subproblems are co-ordinated to obtain the overall sensitivity information. Using this approach, we can not only obtain the overall effect that a small change in a parameter has on the optimum solution of a problem (or system) but also its local effects on the subproblems (or subsystems). A simple two-bar truss example demonstrates the approach.


Author(s):  
H. Torab

Abstract Parameter sensitivity for large-scale systems that include several components which interface in series is presented. Large-scale systems can be divided into components or sub-systems to avoid excessive calculations in determining their optimum design. Model Coordination Method of Decomposition (MCMD) is one of the most commonly used methods to solve large-scale engineering optimization problems. In the Model Coordination Method of Decomposition, the vector of coordinating variables can be partitioned into two sub-vectors for systems with several components interacting in series. The first sub-vector consists of those variables that are common among all or most of the elements. The other sub-vector consists of those variables that are common between only two components that are in series. This study focuses on a parameter sensitivity analysis for this special case using MCMD.


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