Webinar Summary

Optimization is frequently implemented by people whose educational background is in Operations Research or Industrial Engineering, but not Computer Science. This often results in practitioners who develop their own best practices based on trial and error while remaining silo-ed away from techniques that are common in typical IT organizations. Moreover, there is a tendency to think of optimization projects as consisting of a “hard” mathematical engine that can then be industrialized by an “easy” integration and polishing process. The theme of this talk is that “getting the MIP equations right” is just one piece of a much larger puzzle. Optimization engines present integration, maintenance, and ease-of-use challenges that can easily dwarf the man-hours spent on the core mathematics. Luckily, the tools to address these challenges don’t need to be invented from scratch and we will introduce some of the solutions and tools to help guide businesses through implementation.


Presented Materials

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