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.
This talk will provide a different perspective based on the experience of two entrepreneurs who have been building commercial optimization tools since the late 90’s. Mike Watson and Pete Cacioppi worked together at the supply chain optimization company LogicTools (which was acquired by ILOG, then IBM, and the IP eventually sold to LLamasoft). Pete then spent time building the optimization tools at Opalytics (which was acquired by Accenture). And, they are now back together at Opex Analytics building optimization tools.
Together, they discuss six lessons they have learned developing Mixed-Integer Programming based applications.
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