Dynamic programming is an algorithmic technique used to solve certain optimization problems where the object is to find the best solution from a number of possibilities. It uses a so called ‘bottom-up’ approach, meaning that the problem is solved as a set of sub-problems which in turn are made up of sub-sub-problems.Sub-problems are then selected and used to solve the overall problem. These sub-problems are only solved once and the solutions are saved so that they will not need to be recalculated again. Whilst calculated individually, they may also overlap. When any sub-problem is met again, it can be found and re-used to solve another problem. Since it searches all possibilities, it is also very accurate. This method is far more efficient than recalculating and therefore considerably reduces computation. It is widely used in computer science and can be applied for example, to compress data in high density bar codes.

Dynamic programming is most effective and therefore most often used on objects that are ordered from left to right and whose order cannot be rearranged. This means it works well on character chains for example.