Geodesic
Parametric Semidifferentiability of Minimax of Lagrangians: Averaged Adjoint Approach
Journal of convex analysis, Tome 24 (2017) no. 4, pp. 1117-1142
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A standard approach to the minimization of a constrained objective function in the presence of equality constraints in Mathematical Programming or of a state equation in Control Theory is to introduce Lagrange multipliers or an adjoint state. The initial minimization problem is equivalent to the minimax of the associated Lagrangian.
Classification : 49K20, 49K27, 49K35, 49K40, 49Q10, 49Q12
Mots-clés : Minimax, Lagrangian, sensitivity analysis, semidifferential, averaged adjoint, shape, topological derivatives, optimal control, mathematical programming 
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     author = {M. C. Delfour and K. Sturm},
     title = {Parametric {Semidifferentiability} of {Minimax} of {Lagrangians:} {Averaged} {Adjoint} {Approach}},
     journal = {Journal of convex analysis},
     pages = {1117--1142},
     year = {2017},
     volume = {24},
     number = {4},
     url = {http://geodesic.mathdoc.fr/item/JCA_2017_24_4_JCA_2017_24_4_a3/}
}
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M. C. Delfour; K. Sturm. Parametric Semidifferentiability of Minimax of Lagrangians: Averaged Adjoint Approach. Journal of convex analysis, Tome 24 (2017) no. 4, pp. 1117-1142. http://geodesic.mathdoc.fr/item/JCA_2017_24_4_JCA_2017_24_4_a3/