If a problem can be solved by combining optimal solutions to non-overlapping problems, the strategy is called _____________

The strategy described in the question is called Dynamic Programming. This technique is particularly effective in solving complex problems by breaking them down into simpler subproblems that are easier to manage.

In dynamic programming, we focus on optimizing a solution by storing the results of already computed values to avoid unnecessary recalculations, thus saving time and resources. It is especially useful for problems involving overlapping subproblems and optimal substructure.

By solving each subproblem just once and storing the solutions, we can build up the solution to the overall problem systematically. Classic examples of problems that can be approached using dynamic programming include the Fibonacci sequence, Knapsack problem, and shortest path problems like Dijkstra’s algorithm. This strategy ensures that we are constructing the overall solution from optimal components, thereby yielding a globally optimal solution when the subproblems are combined.