Learn how to explain dynamic programming to a beginner in algorithms using simple examples and tips. Discover the trade-offs and challenges of this technique.

To apply dynamic programming to a problem, you need to follow four steps: define the subproblems, write a recurrence relation, initialize the base cases, and fill in the table.

The most difficult part of dynamic programming is acquiring an understanding of a problem's subproblems and recurrence relations. It's amazing how difficult it can be to formulate DP solutions de novo ...

Figures Figure 1. Dynamic programming examples with dependences between stages. (a) the Viterbi algorithm and (b) the LCS algorithm. Figure 2. Parallelization algorithm using rank convergence. (a) the ...

For a dynamic lot sizing problem involving time-varying deterministic demand of a single item, Wagner and Whitin (1958) have developed an efficient regeneration-point dynamic programming (DP) approach ...