Both optimization methods have one thing in common. At the end of the process, they provide you with a list of model mutations from the stored data. Here you can find the details of the controlling optimization result and the associated value assignment of the optimization parameters. This list is organized in descending order. You can find the assumed best solution shown in the first line. For this, the optimization result with its determined value assignment is closest to the optimization criterion. All add-on results have a utilization < 1. Furthermore, once the analysis is completed, the program will adjust the value assignment to that of the optimal solution for the optimization parameters in the global parameter list.
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