Optimization Settings

As soon as you activate the Optimization & Costs / CO₂ Emission Estimation add-on, you can access the Optimization Settings function in the "Calculate" menu.

01 Entering Optimization Settings

It opens the "Optimization Settings" dialog box, where you can control and run the optimization process. All information is managed in the "Main" tab.

02 Dialog Box "Optimization Settings"

Optimization

The "Active" check box is not selected by default. Thus, no optimization is performed. To activate the optimization task, select the check box. After checking the other settings, you can start the optimization by closing the dialog box; just click the "OK and Calculate All" button.

Optimization Parameters

In this section, you can define the boundary conditions of the optimization task. The parameters control the optimization process and provide the framework for the output.

Keep best number of model mutations

The value determines how many of the best possible parameter constellations for the analyzed model mutations are displayed during and after the optimization in the "Optimization" table. There are ten variants preset for the output.

Optimize on

In the list, you can select from various objectives that determine the optimum of the optimization task. As usual in construction, all these criteria describe the minimum model response to certain boundary conditions of the analysis.

03 Selecting Target for Optimization

The program tries to find the appropriate parameters to achieve the minimum result for weight, deformation, cost, or CO₂ emissions. You can use the "Min./Max. Global Parameters" options as user-defined criteria for the formulas that you have entered in the list of Global Parameters .

Optimizer

In the list, you can select the algorithm for solving the optimization problem. The program provides three different solution methods.

• All mutations: In a batch process, all possible model variants ("mutations") are calculated one by one. The result is evaluated for the next step and sorted accordingly in the "Optimization" table . The complete analysis of all mutations has the advantage that the possible optimum parameter configurations are found. At the same time, this form of analysis requires a relatively long calculation time, as all mutations are analyzed.
• Percentage of random mutations: This process first determines a uniform, random distribution of the parameter states for the percentage fraction of all possible model mutations, which you can specify under "Number of random mutations". All parameter constellations determined in this way from each parameter effective range have the same probability. All these constellations are then calculated one by one in a batch process, evaluated for the next step, and sorted accordingly in the "Optimization" table . Depending on the analyzed set of mutations, this form of analysis is comparatively fast, but cannot necessarily find all optimal situations due to the random, uniform distribution of the parameter constellation.
• Particle swarm: This method simulates the behavior of a swarm of animals looking for food or a resting place. The method was developed for the optimization of nonlinear functions. A short description can be found here Wikipedia article. This method also allows you to specify the percentage of random mutations in order to find the best possible parameter configuration with fewer mutations.

Values to Optimize

This section contains an overview table with all optimization parameters listed in the Global Parameters dialog box. The number of possible "states" indicates how many variations are possible for each parameter. They result from the effective ranges and are always about 1 greater than the value specified for the global parameters in the "Steps" column.

Use the button at the bottom right to jump to the "Global Parameters" dialog box to check the optimization parameters. The button becomes accessible when you click in a table cell.

The "Number of optimization mutations" at the end of the table represents the computationally possible parameter constellations from the complete analysis of all optimization parameter states for all optimization parameters. If this number is 0, there are no parameters to optimize; the program cannot start the optimization.