An investigation of due-date assignment using workload information of a dynamic shop

This study investigates a dynamic approach that assigns due-dates to jobs based on workload information, where workload is expressed in two forms: proportional workload function (PWF) and cumulative distribution function (CDF). Two job shop structures single-machine and eight-machine shops were simulated and compared using the SLAM II package. Four combinations of due-date assignment methods and dispatching rules are investigated. The results suggest that assigning due-dates based on the job content and the workload information can lead to lower mean tardiness than assigning due-dates based merely on the job content. The results further indicate that the form in which workload information is used in assigning due-dates and the complexity of the shop structure affect shop performance. In general, the CDF model dominated the PWF model in both simple and complex shop structure environments for both dispatching rules. Another conclusion drawn from this study is that the degree of shop performance improvement does not depend on the complexity of the shop structure. Conditions have been identified under which workload information is most and least critical. Under some of the scheduling combinations, the difference in shop performance between the CDF and PWF was small, which calls for further information value analysis by schedulers before deciding on which of the two models to use.