Model Pane
Model Summary
The top of the pane summarizes the model as it is currently defined. Each row reflects a section of the RASON model and updates automatically as the model is edited.
Optimization Simulation Data Science Calculation Any model type
| Node | Applies to | Description |
|---|---|---|
| Model Name | Any | The root node shows the model name and the model type (optimization, simulation, calculation, or datamining). |
| Objective | Opt | Displays the objective formula and its sense for an optimization model. |
| Variables | Opt | The number of decision variables defined in the optimization model. |
| Constraints | Opt | The number of constraints defined in the optimization model. |
| Uncertain Variables | Sim | The number of uncertain variables defined in the simulation model. |
| Uncertain Functions | Sim | The number of uncertain functions defined in the simulation model. |
| Data entries | Any | The number of data objects or arrays defined in the data section of any model type. |
| Formulas | Any | The number of intermediate formulas defined in the formulas section of any model type. |
Diagnosis Results
The Diagnosis Results branch appears after a model diagnosis is performed on an optimization or simulation model (only). Diagnosis classifies the model and reports the characteristics that determine which Solver engine can be used.
Applies to: Optimization Simulation
| Node | Applies to | Description |
|---|---|---|
| Type | Opt Sim | The problem class identified by the diagnosis. |
| Model Type | Opt | The diagnosed structure of an optimization model. This field does not appear for simulation models. LP Convex indicates a linear, convex program, which can be solved by the fast and reliable linear programming engine. Other classifications for optimization models include LP/MIP, QP, NLP, and Non-Convex. |
| Variables | Opt | The total count of decision variables in the optimization model seen by the diagnosis. |
| Linear Vars | Opt | The number of variables that appear in the optimization model, only in linear terms. |
| Smooth Vars | Opt | The number of variables that appear in smooth (continuous, differentiable) nonlinear functions, in the optimization model. |
| Integers | Opt | The number of variables constrained to integer values in the optimization model. |
| All Functions | Opt | The total number of functions in the optimization model, counting the objective and all constraints. |
| Linear Functions | Opt | The number of those functions that are linear. When this equals All Functions, the model is fully linear. (Optimization models only.) |
| Sparsity | Opt | The percentage of zero coefficients in the model’s coefficient matrix. Higher sparsity generally allows faster solves. (Optimization models only.) |
| Uncertain Variables | Sim | The number of uncertain variables appearing in the simulation model. |
| Uncertain Functions | Sim | The number of uncertain functions appearing in the simulation model. |
| Warnings (n) | Opt Sim | An expandable branch listing any warnings raised during diagnosis. The number in parentheses is the warning count. |
Note: The Diagnosis Results and Warnings branches are only shown after a diagnosis has been run. Before diagnosis, the pane displays the model summary only.