An uncertainty-based approach is undertaken to deal with multipoint wing aerostructural optimization. The flight points are determined by the quadruple set of parameters: Mach number, cruise altitude, carried payload, and flight range. From this set, the payload and range are modeled as probabilistically uncertain based on U.S. flight data for the operations of an A320 aircraft. The fuel burn is selected as the performance metric to optimize. Structural failure criteria, aileron efficiency, and field performance considerations are formulated as constraints. The wing is parametrized by its planform, airfoil sections, and structural thickness. The analyses disciplines consist of an aerostructural solver and a surrogate-based mission analysis. For the optimization task, a gradient-based algorithm is used in conjunction with coupled adjoint methods and a fuel burn sensitivity analytical formula. Another key enabler is a cost-effective nonintrusive uncertainty propagator that allows optimization of an aircraft with legacy analysis codes, within a computational budget.