Dear Gurobi Support Team,
For your information, we are currently using the Gurobipy package (version 10.0.2) for modeling optimization problems and making optimization calls. We are running these on a Gurobi Cloud cluster and using Python (version 3.11.4).
In this context, we aim to perform asynchronous optimization calls in our cloud environment. We have three main objectives, listed in decreasing order of criticality for our application:
- To allow the halting of the optimization process and the return of the solution found up to the point of halting.
- To enable the simultaneous execution of multiple problems on the same cluster, while limiting the number of threads per problem.
- To allow other operations to be performed while the optimization process is ongoing (we understand that this can also be achieved through native Python methods).
We are aware that this functionality is implemented through the
GRBModel.optimizeasync() method, as mentioned in the documentation. However, it appears that this is not available (at least not under that name) in the Gurobipy package, but only in APIs for other languages like Java and C++.
Could you please guide us on how to utilize the functionalities provided by this method in Python?
Thank you for your assistance.
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