New approaches to due date assignment in job shops

• Published in: European journal of operational research 2008-05, Vol.187 (1), p.31-45
• Main Authors: Baykasoğlu, Adil, Göçken, Mustafa, Unutmaz, Zeynep D.
• Format: Article
• Language: English
• Subjects: Applied sciences; Comparative analysis; Deadlines; Due date assignment; Exact sciences and technology; Flowtime estimation; Inference from stochastic processes; time series analysis; Inventory control, production control. Distribution; Job shops; Mathematics; Operational research and scientific management; Operational research. Management science; Operations research; Probability and statistics; Sciences and techniques of general use; Simulation; Statistics; Studies; Time series
• ISSN: 0377-2217; 1872-6860
• DOI: 10.1016/j.ejor.2007.02.020

In this study, two new approaches for due date assignment in job shops are evaluated. Proposed approaches use statistical prediction techniques for dynamic prediction of job flowtimes in a job shop environment as the job arrives to the shop floor. Primary objective of this research is to compare the performance of the proposed due date assignment model ( PDDAM) with several conventional due date assignment models ( CDDAM). For this purpose, simulation models are developed and comparisons of the PDDAM and CDDAM are made in terms of the mean absolute percent error ( MAPE), mean percent error ( MPE) and mean tardiness ( MT). Simulation experiments showed that for many test conditions, PDDAM dominates CDDAM. Therefore, case by case findings are summarized in the paper.