The end users of many analytics applications want to press the “Solve” button in a browser-based application and get a quick response to their business challenge. For example, an end user may want to spend at most a few seconds to create a production schedule for a business operation, or quickly assign people to jobs. Princeton Consultants has built a lightweight Python framework that simplifies the delivery of the back-end server for such applications. This avoids the complexity of other frameworks that are more suited for applications where the analytics process is computationally expensive. In this tutorial at the INFORMS Business Analytics Conference, Irv will demonstrate our best practices for developing analytics applications in terms of processes, Python libraries, and development tools, using optimization as a motivating example.
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