RT journal article
T1 Robust penalty function method for an uncertain multi-time control optimization problems
A1 Jayswal, Anurag
A1 Preeti
A1 Arana Jiménez, Manuel
A2 Estadística e Investigación Operativa
K1 Absolute value penalty function method
K1 Convexity Multi-time control optimization problem
K1 Robust necessary optimality conditions
K1 Robust optimal solution
AB This paper gives some new results on multi-time first-order PDE constrained control optimization problem in the face of data uncertainty (MCOPU). We obtain the robust sufficient optimality conditions for (MCOPU). Further, we construct an unconstrained multi-time control optimization problem (MCOPU) corresponding to (MCOPU) via absolute value penalty function method. Then, we show that the robust optimal solution to the constrained problem and a robust minimizer to the unconstrained problem are equivalent under suitable hypotheses. Moreover, we give some non-trivial examples to validate the results established in this paper
PB Elsevier
SN 1096-0813
YR 2022
FD 2022-01-01
LK http://hdl.handle.net/10498/40417
UL http://hdl.handle.net/10498/40417
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 06-nov-2026