Prescriptive Analytics

Prescriptive methodologies not only look into the future to predict likely outcomes but they also attempt to shape the future by optimizing the targeted business objective while balancing constraints. Analytic techniques that fall into this category include optimization techniques such as linear programming, goal programming, integer/mixed-integer programming, and search algorithms; artificial intelligence optimization techniques such as genetic algorithms and swarm algorithms; and multi-criteria decision models such as analytic hierarchy process, analytic network, process, multi-attribute utility and value theories, and value analysis. The following tutorials walk you through common forms of prescriptive analytics.

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