A probabilistic cost-based due date assignment model for job shops

Abstract

In this paper, a cost-based due date assignment methodology is proposed. The method uses two pre-specified parameters: an estimate of the job flow time and the probability of the job being tardy. An optimization model is presented to find the best tardiness probability of the job based on a total cost function involving the work-in-process inventory and the tardiness costs. Using the results of the correlation analysis performed on a wide set of shop, job and job’s route related variables, ten models are constructed to estimate the flow time of a job in the shop. The models are then compared based on the simplicity of the model and the standard deviation of the estimate errors. One of the models is recommended and tested to check if it can be used in different shop scenarios. As a result, it is observed that the model performs satisfactorily in all the shop conditions considered in this study.