Time: 10h00 - 11h00, Wednesday, July 31st, 2024

Location: Room 617, building A6, Institute of Mathematics (18 Hoang Quoc Viet, Cau Giay, Hanoi)

Abstract: In this talk, we consider a polynomial optimization problem in which  the constraints involve uncertain parameters and either the solutions of another optimization problem or variational inequalities. We employ the deterministic robust approach to examine the bilevel programming and equilibrium constrained  polynomial optimization problems under data uncertainties by providing  lower bound approximations  and convergences of  relaxations for the robust bilevel and equilibrium constrained polynomial optimization problems. More precisely, we show that the optimal values of relaxation problems are lower bounds of the global optimal value of the robust bilevel or equilibrium constrained polynomial problem and these optimal values of relaxations converge to the global optimal value of the underlying problem under additional assumptions. An application to electric vehicle charging scheduling problems will also be presented.