> For the complete documentation index, see [llms.txt](https://docs.fabricplan.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.fabricplan.com/user-guide/8-optimization-in-planning/8.2-direction-based-optimization.md). # 8.2 - Direction-based optimization In this tutorial, you learn to use direction based optimization, define constraints, and apply optimized values to your planning sheet. ### Prerequisites 1. A planning sheet is created with measures, row, and column dimensions assigned.

In this example, *PY Profit* is the difference between *PY Revenue*, *PY Purchase*, and *PY Transportation*. These measures are reported prior year actuals from the semantic model.

2. Create data input measures (Independent variables). Native measures from the semantic model can't be edited. Before running optimization, create copies of the native measures that require optimization. In the **Planning** ribbon, go to **Insert Column > Number**. Select **Copy from another series**. Select the native measure to copy, in this case, *PY Revenue*.

Enter the *Revenue Plan* as the measure name. Set **Insert as** to **Visual Measure**. Ensure **Input type** is **Number**, row and column aggregation types are **Sum**, and **Distribute parent value to children** is selected.

Select **Create**. In this example, the same steps are repeated to create *Purchase Plan* from *PY Purchase*, and *Transportation Plan* from *PY Transportation*. 3. Create a formula measure (Dependent variable). The formula measure is the dependent variable. The independent variables are optimized to achieve the target value assigned to the dependent variable. In the **Planning** ribbon, go to **Insert Column > Formula**.

Enter the *Profit Plan* as the measure name and enter the formula. Set **Insert as** to **Visual Measure**. Ensure the **input type** is **Number**. Row and column aggregation types must be set to **Formula**.

Select **Create**. 4. Manage Column Display To view all the measures in the planning sheet, in the **Planning** ribbon, go to **Show Columns** and select the settings icon.

To focus on the measures required for optimize, deselect the native measures from the semantic model. In this example, the visual measures are *Profit Plan*, *Revenue Plan*, *Purchase Plan*, and *Transportation Plan*. Only the selected measures are displayed in the planning sheet.

5. Configure Aggregation Settings. Select the aggregation icon(Σ). Set **Row Grand Total** and **Row Subtotal** to **Top**.

### Configure optimizer (Direction-based) In this previous section, Optimize is used to achieve a specific target value. In this section, the steps outline how to achieve the maximum value for *Profit Plan* within specified constraints. 1. Select the cell that shows the total Profit Plan. 2. Select **Optimize**.

3. Set **Objective** to **Target**, then select the independent variables, that is, the data input measures (*Revenue Plan*, *Purchase Plan*, and *Transportation Plan*) in the **Variables to Update** section. Select **Next**.

4. Select **Add Constraint** to define thresholds for the independent variables. Refer to Add constraints to know more about configuring thresholds. 5. Select **Run** to start the Optimizer.

6. The **Target Value** of **55m** is achieved by simulating values of *Revenue Plan*, *Purchase Plan*, and *Transportation Plan* (the independent variables). Review the simulated values.

{% hint style="success" %} If the target value isn't achieved, users can change the following parameters and rerun the Optimizer. * **Strategy**: (from 1 to 10) defines the size of adjustments made while trying to achieve the target. * **Tolerance %**: (from 0.1 to 20) is the acceptable deviation between the target value and the optimized value. * **Number of iterations**: (from 1,000 to 10,000) refers to the total number of times the Optimizer updates its internal mathematical model to move closer to the target value by changing the values of the independent variables. {% endhint %} 1. Select **Apply** to replace the values of the data input measures with the optimized values.

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