Prescriptive Analytics & Optimization

Prescriptive analytics differs from descriptive and predictive analytics in that prescriptive models yield a course of action to follow. That is, the output from a prescriptive model is a plan for management to follow. By using optimization models and other readily available tools, we can determine the best near-term outcomes and make the best decisions for our organizations.

As we evaluate business objectives, key metrics such as profitability improvement, cost reductions, and client satisfaction can be optimized with prescriptive analytics. During this program, applications in business including production planning, location analysis, supply chain design, transportation, marketing/product design and financial portfolio analysis will be discussed. Additionally, the use and application of rule-based systems and heuristics with an emphasis on optimization modeling of real business problems will be explored and tested. We will utilize hands-on real-world case studies using open-source software (Open Solver) in Microsoft Excel, R for Optimization, and AMPL – algebraic modeling system.