Multiple objective optimization tasks are everywhere, ranging from cost and quality to technical criteria such as lift and drag of an airfoil or tumble and mass flow of a fuel injector.
Often, there is not “the” single optimal solution, but instead a multitude of possible compromises, for which one criterion can only be improved at the expense of another criterion. These compromise solutions are located on the so-called Pareto frontier, which can be identified by means of a suitable optimization algorithm. Using this approach, you can then select a suitable solution from the Pareto frontier.
ClearVu Global Optimizer includes a powerful extension for efficient multiple objective optimization, covering the frontier with as little function evaluations as possible while also providing a broad and complete coverage of the frontier. This guarantees all extreme solutions to be found as well.
As a result, this method can also be used for computationally expensive and high-dimensional objective functions.
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