@article {1487,
	title = {Periodic Due Date Assignment with Family Setups},
	journal = {INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE},
	volume = {26},
	year = {2019},
	pages = {0{\textendash}0},
	issn = {-},
	author = {Sertdemir, Sevilay and Ali Tamer {\"U}nal and D{\"U}ZG{\.I}T, ZEHRA}
}
@article {1488,
	title = {A parallel machine lot-sizing and scheduling problem with a secondary resource and cumulative demand},
	journal = {International Journal of Production Research},
	volume = {56},
	year = {2018},
	pages = {3344-3357},
	abstract = {<p>We investigate a parallel machine multi-item lot-sizing and scheduling problem with a secondary resource, in which demands are given for the entire planning horizon rather than for every single period. All-or-nothing assumption of the discrete lot-sizing and scheduling problem is valid so that a machine is either idle or works at full capacity in a period. The objective is to minimise the number of setups and teardowns. We prove that the problem is NP-hard and present two equivalent formulations. We show some properties of the optimal objective value, give optimality conditions and suggest a heuristic algorithm. We discuss and formulate two possible extensions related to real-life applications. Finally, we carry out computational experiments to compare the two formulations, to determine the effect of our proposed modeling improvements on solution performance, and to test the quality of our heuristic.</p>},
	doi = {10.1080/00207543.2017.1406675},
	url = {https://doi.org/10.1080/00207543.2017.1406675},
	author = {Murat G{\"u}ng{\"o}r and Ali Tamer {\"U}nal and Z C Ta{\c s}k{\i}n}
}
@article {1490,
	title = {A probabilistic cost-based due date assignment model for job shops},
	journal = {International Journal of Production Research},
	volume = {31},
	year = {1993},
	pages = {2817-2834},
	abstract = {<p>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{\textquoteright}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.</p>},
	doi = {10.1080/00207549308956902},
	url = {https://doi.org/10.1080/00207549308956902},
	author = {A. C. KAPLAN and Ali Tamer {\"U}nal}
}
