Optimal Sequential Sampling Plans Using Dynamic Programming Approach

In this paper we proposed a dynamic programming procedure to develop an optimal sequential sampling plan. A suitable cost model is employed for depicting the cost of sampling, accepting or rejecting the lot. This model is based on sequential approach. A sequential iterative approach is used for modeling the cost of different decisions in each stage. In addition a backward recursive algorithm is developed to solve the dynamic programming. On the other hand, the purpose of this paper is to introduce a new sequential acceptance sampling plan based on dynamic programming. At the end of this paper a numerical example is solved to show how this model works and then sensitivity analyses of main parameters of acceptance sampling model are carried out.