Many optimization problems in applications can be formulated using several objective functions, which are conflicting with each other. This leads to the notion of multiobjective or multicriterial optimization problems. Here, we investigate the application of the Euclidean reference point method in combination with model-order reduction to multiobjective optimal control problems. Since the reference point method transforms the multiobjective optimal control problem into a series of scalar optimization problems, the method of proper orthogonal decomposition (POD) is introduced as an approach for model-order reduction.
|ScienceOpen disciplines:||Applied mathematics, Applications, Statistics, Data analysis, Mathematics, Mathematical modeling & Computation|
|Keywords:||Multiobjective Optimal Control, Certified POD, POD basis updates, Multiobjective Optimization|