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These charts showcased metrics like backlog, orders processed by value ($) and volume, aging buckets, team utilization, cost of operations, etc. The model was created in AnyLogic simulation software / Road Traffic. You can create several experiments for the same model with alternative model settings. A group of model settings is called an experiment, and experiments are displayed at the bottom of the model branch in the workspace tree. Start the flowchart with the train generating TrainSource block, then add TrainMoveTo block placing it close to the first block. Model simulation has a set of specific settings. We will use them to define the train logic. Add the following blocks to the flowchart: TrainSource, TrainMoveTo, TrainDecouple, TrainCouple, TrainDispose. Click the Run control in the model window to start the optimization process. You will see the model window opened, showing the UI you have created for this experiment. This view was used to display the impact of an AI engine on the process without shooting too many numbers at the viewer. Define the model logic using AnyLogic Rail Library blocks. Right-click (macOS: Ctrl + click) the optimization experiment in the Projects view and choose Run from the context menu. Specify the Agent type name: MC and the Agent name: center.
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We are creating a new type of agent and do not need to use any templates. Then we surrounded the high-level process view images with panes containing charts to provide an excellent visual interface. We need only one maintenance center that will send transport to turbines for scheduled maintenance and any failures/repairs. Then, we created motion paths to let the orders move over the images of sub-processes to give them a progressive motion feel. We then saved these slides as images to be used in the model. We created slides of as-is and to-be scenarios, each containing only the essential sub-processes. We again used this logic to hide and unhide in creating a high-level overview of the overall process. E.g., When the model starts, one will see the toggle button image in the off state, but when you click on the image, the off-state image is set to invisible, and the on-state image will become visible and vice versa. We used programming to hide and unhide the images. Instead, we used images of the two states of a toggle button, i.e., on and off. While creating the switch, we didn’t use a button control as it looked very basic. At this juncture, the work we did to make the switch to toggle between as-is and to-be scenarios and view areas, that I learned in the AnyLogic in 3 days book, was to become the base of our presentation layer. We will use this experiment to find exact locations of the objects taking into account the data derived from the results of the Greenfield Analysis experiment. We took a step back and decided to create a separate presentation layer over what we had built. Network optimization is another analytical method of optimizing your supply chain.