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Scalarization methods are a category of multiobjective optimization (MOO) methods. These methods allow the usage of conventional single objective optimization algorithms, as scalarization methods reformulate the MOO problem into a single objective optimization problem. The scalarization methods analysed within this thesis are the Weighted Sum (WS), the Epsilon-Constraint (EC), and the MinMax (MM) method. After explaining the approach of each method, the WS, EC and MM are applied, a-posteriori, to three different examples: to the Kursawe function; to the ten bar truss, a common benchmark problem in structural optimization; and to the metamodel of an aero engine exit module.
The aim is to evaluate and compare the performance of each scalarization method that is examined within this thesis. The evaluation is conducted using performance metrics, such as the hypervolume and the generational distance, as well as using visual comparison.
The application to the three examples gives insight into the advantages and disadvantages of each method, and provides further understanding of an adequate application of the methods concerning high dimensional optimization problems.