I learned this morning from my LinkedIn feed that January 29 is national puzzle day. So, we decided to put out a fun blog to mark the occasion. We have tried to solve Sudoku using a Mixed Integer Program (MIP). This blog is unrelated to Supply Chain although we use the technique used here to solve supply chain problems. Please enjoy!
An optimization model does the same; it calculates the decisions based on the stated preferences and constraints in the model. That can sometimes have the inadvertent effect of finding new pathways, a road less, if ever, traveled.
Most folks involved in Sales and Operations Planning (S&OP) for supply chain management have heard the terms “optimization” or “linear programming” with regards to supply planning and have cringed at the sound. Over the past few years a new “cringe” worthy term has emerged – “machine learning” which is sometimes used with the term predictive
The term ‘optimization’ can and does have different meanings to different groups. For the folks who build and develop scheduling algorithms, creating the best schedule is defined in terms of cost criteria – perfectly logical. For business settings (from manufacturing to hospitals) optimization refers to the entire process. Let’s look at the scheduler’s world to