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The latter is a convex polytope representing all the possible forces and moments that can be attained by the aircraft control effectors and flight control system . The constraints (and, optionally, the objective function) of such optimization problem are obtained by exploiting the geometric properties of the Attainable Moment Set (AMS). This paper presents a novel generic trim problem formulation, in the form of a constrained optimization problem, which employs forces and moments due to the aircraft control surfaces as decision variables. Trimming a dynamic system means finding the combination of input and state variables values which set the system in a steady-state condition. More conventional trim applications for minimum total drag and for assigned angle of elevation are also explored. Results show that the method is able to capitalize on the angle of attack or the throttle setting to obtain the control surfaces deflections which maximize control authority in the assigned direction. Control authority is defined on the basis of control forces and moments, and interpreted geometrically as a distance within the AMS. The latter can be intended as equivalent to the classic concept of minimum control effort. Novel trim applications are presented to maximize control authority about the lift and pitch axes, and a “balanced” control authority. The methodology is applied to an innovative box-wing aircraft configuration with redundant control surfaces, which can partially decouple lift and pitch control, and allow direct lift control. Trim control forces and moments are mapped to control surface deflections at every solver iteration through a linear programming formulation of the direct Control Allocation algorithm. the set of all control forces and moments attainable by the control surfaces, is used to define linear equality and inequality constraints for the control forces decision variables. The geometry of the Attainable Moment Set (AMS), i.e. This paper presents a generic trim problem formulation, in the form of a constrained optimization problem, which employs forces and moments due to the aircraft control surfaces as decision variables.