scholarly journals $ \varepsilon $-DIRECTIONAL DERIVATIVE OF A MARGINAL FUNCTION IN PARAMETRIZED CONVEX PROGRAMMING

10.5109/13417 ◽  
1991 ◽  
Vol 24 (3/4) ◽  
pp. 177-183
Author(s):  
Shunsuke Shiraishi
Keyword(s):  
Convex Programming ◽  
Directional Derivative ◽  
Marginal Function

scholarly journals Sufficient Optimality and Sensitivity Analysis of a Parameterized Min-Max Programming

2012 ◽  
Vol 2012 ◽  
pp. 1-9
Author(s):  
Huijuan Xiong ◽  
Yu Xiao ◽  
Chaohong Song
Keyword(s):  
Sensitivity Analysis ◽  
Objective Function ◽  
Directional Derivative ◽  
Second Order ◽  
Marginal Function ◽  
Feasible Set ◽  
Second Order Directional Derivative ◽  
Computation Formula ◽  
Clarke’S Subdifferential

Sufficient optimality and sensitivity of a parameterized min-max programming with fixed feasible set are analyzed. Based on Clarke's subdifferential and Chaney's second-order directional derivative, sufficient optimality of the parameterized min-max programming is discussed first. Moreover, under a convex assumption on the objective function, a subdifferential computation formula of the marginal function is obtained. The assumptions are satisfied naturally for some application problems. Moreover, the formulae based on these assumptions are concise and convenient for algorithmic purpose to solve the applications.

Mixed H2/H∞ control via convex programming

1991 ◽  
Author(s):  
Mario A. Rotea ◽  
Pramod P. Khargonekar
Keyword(s):  
Convex Programming

A framework for pulmonary fissure segmentation in 3D CT images using a directional derivative of plate filter

2020 ◽  
Vol 173 ◽  
pp. 107602 ◽  
Author(s):  
Hong Zhao ◽  
Berend C. Stoel ◽  
Marius Staring ◽  
M. Bakker ◽  
Jan Stolk ◽  
...  
Keyword(s):  
Directional Derivative ◽  
Ct Images ◽  
3D Ct ◽  
Fissure Segmentation ◽  
Plate Filter
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