m.soomar1255 Posted Friday at 05:42 PM Posted Friday at 05:42 PM Hello everyone, I am sharing a Simio simulation model and would greatly appreciate guidance from the Simio community aSample Model.rarSample Model.rarnd the Simio development team. In this model, my goal is to implement a Genetic Algorithm (GA)–based optimization, similar to Simio’s built-in OptQuest optimizer, but developed externally in Python. The idea is to use Simio scripted steps to control simulation runs, exchange data with the GA in real time (or iteratively), and submit optimized decision variables back into Simio. The intended approach is as follows: Use scripted steps to run the simulation Send decision variables and performance measures from Simio to a Python-based GA Execute the GA externally to generate new candidate solutions Feed the optimized solutions back into Simio for subsequent simulation runs I am looking for help and best-practice recommendations on: The most effective way to integrate Simio with Python for this purpose Suitable data exchange mechanisms (e.g., files, sockets, APIs, or other supported approaches) How to structure scripted steps to support an external optimization loop efficiently Any limitations or recommended patterns when implementing custom optimizers alongside Simio I am sharing the model so that others can review it and provide more concrete suggestions. Any support, examples, or guidance from experienced users or the Simio team would be highly appreciated. Thank you in advance for your time and help. Best regards,
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