many real-world problems (e.g. scheduling, resource allocation, planning, logistics) share a common structure: you have decisions to make, constraints to satisfy, and goals to optimize. Yet most implementations (and developers) approach these with ad-hoc algorithms that quickly become unmaintainable as complexity grows.

Constraint programming and operations research offer a different paradigm. Instead of writing step-by-step algorithms, you declare your problem: the variables, the constraints, and what you're trying to optimize. A solver (or-tools highlighted) then finds solutions for you, often exploring vast search spaces efficiently.

In this introductory talk, MiniZinc will be showcased, a high-level constraint modeling language, to explore these concepts through practical examples covering problems like timetabling, where seemingly simple requirements ("assign teachers to timeslots") explode into complex webs of constraints that naive approaches struggle with.

disclaimer: ai was used to write the description.
note: can be fit to a short session if need be.