Solution: Cheapest Flights Within K Stops

Explore how to determine the minimum travel cost from a source to a destination city with up to K stops using dynamic programming. This lesson guides you through modeling the problem as a shortest path in a weighted graph, applying the Bellman–Ford style algorithm to handle stop constraints efficiently. You'll understand the iterative relaxation process and how to track optimal costs, enabling you to solve similar constrained shortest path problems in coding interviews.