A recursive approach for lot sentencing problem in the presence of inspection errors

ABSTRACT

In this paper, a new sequential acceptance sampling plans in the presence of inspection errors is developed. A suitable profit objective function is employed for optimizing the lot sentencing problem. A backward recursive approach is applied for obtaining the profit of different decisions in each stage of sampling. Required probabilities are obtained using Bayesian rule. A case study is solved for illustrating the application of proposed models and sensitivity analysis are carried out on the parameters of the proposed methodologies and the behaviour of models by changing the parameters are investigated.

KEYWORDS:

• Acceptance sampling plan
• Bayesian inference
• Dynamic programming
• Inspection errors

MATHEMATICAL SUBJECT CLASSIFICATION:

• 65C40
• 65C50