cuopt-server-api-python

You can deploy the cuOpt REST server locally or in cloud environments using specific startup commands. It supports development and production modes, with health checks to verify the server is ready to accept optimization tasks.

Yes, you can use Python requests or curl clients to submit VRP, PDP, LP, and MILP optimization tasks to the cuOpt REST server. The clients submit problem payloads to REST endpoints and poll the server to retrieve the computed solutions.

Submitting a pickup-and-delivery problem to the cuOpt REST API requires formatting the task data into specific payload structures. You send this payload to the REST endpoint and use the Python or curl client to poll for the returned solution.

Yes, the cuOpt REST server supports deployment in both local development and cloud environments. It specifies startup commands and health checks to ensure end-to-end deployment of optimization workloads across different infrastructure setups.

You retrieve optimization results by using Python or curl clients to poll the cuOpt REST server. After submitting your VRP, PDP, LP, or MILP task to the endpoint, the client continuously checks until the computed solution is ready to fetch.