Exploring the applications & benefits of this prescriptive analytics technique across industries & disciplines
What is mathematical optimization and how do organizations across industries use this type of prescriptive analytics? Download our guide to get an overview of the most common and impactful use cases.
Mathematical optimization is a subset of artificial intelligence and a type of prescriptive analytics. It determines ways in which business processes should evolve or be modified, providing implementable solutions with known cost and/or benefit.
What are some of the most common use cases for mathematical optimization? How can this type of prescriptive analytics be applied to lower costs, reduce carbon emissions and build more resilient supply chains? Find out in this Guide.
This Guide is ideal if you:
- Are curious about the different application areas for mathematical optimization
- Want ballpark estimates of value and benefits achieved through optimization
- Want examples where optimization is used in combination with other types of AI techniques, such as machine learning
Mathematical optimization, applied
Optimization complements other AI techniques like machine learning. It enriches the analytics toolbox and is a highly adaptable tool that helps you improve decision making in a broad range of areas and across industries.