Inf8770

Python (with Numpy/Scipy) is great for prototyping. C++ or Java is better if the professor benchmarks for speed. If you use Python, learn PuLP or OR-Tools immediately.

In an era of AI and Big Data, optimization is the hidden engine. Every time you see an Uber matched with a rider, a warehouse robot avoiding a collision, or a Netflix server caching a movie—that is INF8770 in action. Inf8770

Here is your comprehensive guide to not just surviving INF8770, but actually enjoying the process of breaking combinatorial problems. The first lesson of INF8770 is a humbling one. For large-scale problems (think: routing 100 delivery trucks or scheduling a hospital), finding the perfect mathematical solution might take longer than the age of the universe. Python (with Numpy/Scipy) is great for prototyping

But let’s be real: It is also the class where many of us first encounter the existential dread of problems. In an era of AI and Big Data,

Are you currently taking INF8770? What algorithm are you struggling with right now? Let me know in the comments below!

By the end of this course, you will stop seeing a messy spreadsheet. You will see a matrix. You will see constraints. And you will see a path to the optimal solution.