ABSTRACT
Dynamic programming is an optimization technique of multistage decision process. In dynamic programming, a large problem is split into smaller sub problems each of which involve in a few variables. These sub problems are sequentially optimized so as to make the total problem optimal. Discrete and continuous, deterministic as well as probabilistic models can be solved by this method. Thus dynamic programming method is very useful in obtaining optimal solutions of various problems such as inventory. A single constraint problem is relatively simple, but in the problem of more than two constraints more complexities may appear. A dynamic programming problem (DPP) is solved by an objective function which is recurring in nature. The solution of a DPP is based on Bellman’s principle of optimality (recursive optimization technique) which states: An optimal policy has the property that, whatever the initial state and initial decision, the remaining decisions must constitute an optimal policy with regard to the state resulting from first decision..
