Utilizing machine learning to concurrently optimize computing resources and licenses in a high-performance computing environment

A device may receive a job request that requests performance of one or more operations by resources of a high-performance computing environment, and may process the job request, with a policy execution model trained with policy parameters, to identify policies to apply during execution of the job request. The device may process the job request, with a forecast object model trained with job data and profile data, to generate a forecast of resources and licenses required from the high-performance computing environment. The device may process the job request, other job requests, the one or more of the policies, and the forecast, with a heuristic model, to determine a schedule for the job request, and may process the schedule and current constraints on the resources and the licenses, with a linear programming model, to determine an optimized schedule for the job request.