Page Comparison

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1. Open Insight and click Browse (as shown in Figure 1) to choose the directory containing the project(s).  Projects can also be in subdirectories below the directory pointed to;
2. Click Load to populate the left panel with all the available functions defined in the loaded projects;
3. For each of the panels on the right, use the appropriate button to add or remove objectives functions or decision variables from the main function list to the individual panel. For example, click Add objective » to add an objective function to the Objectives panel. Moreover, to move a discrete decision variable back to the main list of objective functions, click « Remove discrete decision variable.
4. In the Objectives panel, the Multi-project Aggregation Method drop-down menu allows you to choose how you want to aggregate process the individual time-step results. The objective function values passed from individual scenarios. By default Insight uses the final value of the specified function as the value of the objective function for each scenario.  The Aggregate over full timeseries checkbox allows you to choose how to setup the objectives. If enabled, the objective needs to be set up so that all values of the global expression are used use the values of the objective function determined at each timestep, rather than just the last value (via the selected statistical function) to give the objective value. If not, the last value of the global expression gives the objective value. You .  You can also remove an objective from the Objectives panel by choosing it from the list and clicking . This will move the objective back to the main objectives list.
5. Choose the number of generations and the population size of each generation. These parameters define how many simulation runs are performed by the optimiser. The required values will depend on the complexity of the optimisation project. If the number of runs is too small, the optimiser will not be given sufficient time to search for the multi-objective optimal set of results.  The population size also sets the maximum number of points on the Pareto front or surface.
6. Specify whether to run the optimisation on your local machine (enable the Run Source optimisation locally radio button), or across server endpoints (using the Run Source optimisation on endpoints radio button). Server endpoints allow you to run the optimisation across several machines simultaneously. Load the endpoints settings file by clicking Load Endpoints and point Insight to the appropriate file. If running Source optimisation on a local machine, set the number of cores to use with the Local server limit scroll button. The number of cores to use depends on the machine you will are using.
7. Save your settings using File » Save Settings. This creates a settings file, which can be used later.

The optimisation is now ready to be run.

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Insight can be configured, set up (to create using a settings file) and run using the command line as well. This link shows some examples of how to use the command line for Insight. Note that an explanation of these commands is provided further down:

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project C:\Insight\test\Example_project.rsproj

OutputExportedOutput $reliabilityNeg

ExportedOutput $unitcost

ExportedOutput $Yieldneg

real $pipecapacity 0 200
real $demand 0 100
real $treatmentcapacity 0 100

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