Changes between Version 13 and Version 14 of Documentation/Howto/OptimizeAnyLogicModels

Timestamp:

05/30/17 12:57:44 (7 years ago)

Author:

abeham

Comment:

fixed link to direct download

Documentation/Howto/OptimizeAnyLogicModels

@@ -17 +17 @@
 First save the model in a new location. Click "Save As..." in the File menu. For the sake of simplicity just put "Supply Chain" in the box that asks for a model name and leave everything else. That way it will save it in a folder called "Models" in your user's directory.
 
-Now download the [http://dev.heuristiclab.com/trac.fcgi/attachment/wiki/Documentation/Howto/OptimizeAnyLogicModels/HL3ExternalEvaluation.jar HL3 External Evaluation Java library] to a place that you remember (e.g. your Downloads directory; you should not download it into the model folder already). Then switch to !AnyLogic 6 again and click the model icon in the project view (should be called "Supply Chain" if you followed the model name suggestion above). In the properties window of this model in the section "Jar files and class folders required to build the model:" click the add button. Choose the file you just downloaded, make sure "Import to model folder is ticked" and click "Finish" to add the library. Save the model.
+Now download the [http://dev.heuristiclab.com/trac.fcgi/raw-attachment/wiki/Documentation/Howto/OptimizeAnyLogicModels/HL3ExternalEvaluation.jar HL3 External Evaluation Java library] to a place that you remember (e.g. your Downloads directory; you should not download it into the model folder already). Then switch to !AnyLogic 6 again and click the model icon in the project view (should be called "Supply Chain" if you followed the model name suggestion above). In the properties window of this model in the section "Jar files and class folders required to build the model:" click the add button. Choose the file you just downloaded, make sure "Import to model folder is ticked" and click "Finish" to add the library. Save the model.
 
 Now we need to add a new experiment which we can run to serve as our evaluation function. The best type of experiment for this task is a "Parameters Variation" experiment, so choose this and choose a name for it, e.g. "!HeuristicLabOptimizationExperiment". Leave everything else as it is and click "Finish". Now we have created a new experiment with which we can optimize the parameters.