A statistical analysis and simulation based approach to an uncertain supplier selection problem with discount option

Abstract

The uncertainties existing in today’s manufacturing environment tends researchers to use statistical and simulation approach to address such stochastic problems. The supplier selection problem has attracted growing interest. One of the crucial issues in supplier selection is product outsourcing. The outsourcing improved the service price by decreasing that, also it reduced the waiting time and increased the customer satisfaction. Furthermore, it improved the company’s core competence. In supplier selection problem, some criteria are effective such as: cost, delivery time, quality. During recent years, various approaches are proposed for supplier selection problem. But in one hand, most of them have considered only single criteria, and on the other hand, some stochastic parameters are assumed to be deterministic. In this study, a statistical method based on design of experiment (DOE) and simulation is presented that minimizes cost and lead times while maximizes quality in the existence of discount. Furthermore, model parameters such as demand, lead time, and rejected products percentage are assumed as stochastic parameters. Finally, the model has been solved using weighted objective method and compromise programming and then the results have been analyzed.