This content introduces the concept of constraint programming, a method used to solve discrete optimization problems declaratively. Unlike imperative programming, which outlines steps to reach an outcome, constraint programming focuses on describing the desired result through variables and constraints. An example of sharing sweets and a real-world problem of scheduling employees are used to illustrate how CP works. Constraints are added to ensure fair work schedules and allocation of roles while optimizing efficiency. A solver interprets the model and produces valid solutions. The article uses Python and CP-SAT to demonstrate solving complex real-world problems, emphasizing the practical application of constraint programming.
https://pganalyze.com/blog/a-practical-introduction-to-constraint-programming-using-cp-sat