Fast Pareto set generation for nonlinear optimal control problems with multiple objectives

Many practical engineering problems involve the determination of optimal control trajectories for given multiple and conflicting objectives. These conflicting objectives typically give rise to a set of Pareto optimal solutions. To enhance real-time decision making efficient approaches are required for determining the Pareto set in a fast and accurate way. Hereto, the current paper integrates efficient multiple objective scalarisation strategies (e.g., Normal Boundary Intersection and Normalised Normal Constraint) with fast deterministic approaches for dynamic optimisation (e.g., Single and Multiple Shooting). All techniques have been implemented as an easy-to-use add-on module of the automatic control and dynamic optimisation toolkit ACADO (both freely available at http://www.acadotoolkit.org). Several algorithmic synergies (e.g., hot-start initialisation strategies) are exploited for an additional speed-up. The features of ACADO Multi-Objective are discussed and its use is illustrated on different multiple objective optimal control problems arising in several engineering disciplines.