Optimal Sequential Sampling Plans Using Dynamic Programming Approach

Abstract

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 that can be adapted to a computer program. At the end of this paper a numerical example is solved to show how this model works.