The focus in our class will be on learning how to model certain kinds of problems as optimization problems, translate them to Excel, and solve them using Solver. We are starting in on optimization modeling this week. If you want to learn more about the math of optimization, there are a number of courses offered in the Math/Stat department such as MOR 3330 (Engineering Operations Research), MOR 4554 (Linear and Integer Optimization) and MOR 4555 (Nonlinear Optimization). If you want to learn more about optimization modeling, consider taking QMM 4400 (Management Science) in the SBA within the friendly confines of Excel. In fact, while data mining and “predictive analytics” is all the rage, when you look into the details you find statistics, simulation, and optimization. ![]() Optimization models are lurking under the hood of many common business applications. I hope to give you a glimpse into the amazing breadth and power of optimization modeling and solver tools available to business analysts. They are fun to do because we get to make Excel and Solver do the hard work of coming up with the answers (once we formulate a good model). These beasts pop up in all kinds of business problems. ![]() ![]() ![]() We’ll see examples of linear, non-linear and integer optimization problems. This is an introduction to optimization using Excel Solver.
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