Let's understand this approach through an example.Ĭonsider an example of the Fibonacci series. The definition of dynamic programming says that it is a technique for solving a complex problem by first breaking into a collection of simpler subproblems, solving each subproblem just once, and then storing their solutions to avoid repetitive computations. The dynamic programming guarantees to find the optimal solution of a problem if the solution exists. Here, optimization problems mean that when we are trying to find out the minimum or the maximum solution of a problem. The main use of dynamic programming is to solve optimization problems. The subproblems are optimized to optimize the overall solution is known as optimal substructure property. Dynamic programming is a technique that breaks the problems into sub-problems, and saves the result for future purposes so that we do not need to compute the result again.
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