Applying Mathematical Optimization in Practice: A Note on Insights from MO Projects

Abstract

Applying mathematical optimization (MO) in industry is still very often done by MO experts. In this contribution, we use an outside-in approach to describe the key requirements for optimization projects to be successfully instantiated within the businesses. We focus on the development and usage of decision support tools for operational, tactical, and strategic planning. They are to be used by business experts with little or no background in mathematical optimization. These people are still experts, e.g., in planning and managing complex supply chains or global production assets. While they are open to new tools and methods, in reality, many optimization projects fail to be handed over to them. We discuss the requirements and best practices for MO projects to overcome the underlying challenges. Several of the findings can be transferred to future applications of MO. These arise around the Industrial Internet of Things (IIoT), particularly focused on real-time applications, large, connected, and interdependent systems.