An available-to-promise stochastic model for order promising based on dynamic resource reservation policy

• Published in: International journal of production research Vol. 61; no. 16; pp. 5525 - 5542
• Main Authors: Qin, Wei, Zhuang, Zilong, Sun, Yanning, Liu, Yang, Yang, Miying
• Format: Journal Article
• Language: English
• Published: London Taylor & Francis 18-08-2023; Taylor & Francis LLC
• Subjects: Available-to-promise (ATP); Customers; Genetic algorithms; maximise expected total profit; order promising; reservation policy; resource allocation; Stochastic models; reservation policy; maximise expected total profit; Available-to-promise (ATP); resource allocation; order promising
• ISSN: 0020-7543; 1366-588X; 1366-588X
• DOI: 10.1080/00207543.2022.2103472

Facing uncertain future customer orders, a pull-based available-to-promise (ATP) mechanism will deteriorate the overall profit since it allocates critical resources only to current customer orders. To prevent current less-profitable customer orders from over-consuming critical resources, this study investigates a push-pull based ATP problem with two time stages and three profit margin levels, and develops a dynamic resource reservation policy to maximise the expected total profit. Then, a corresponding push-pull based stochastic ATP model is established with known independent demand distributions, and the optimal reservation level is derived by the genetic algorithm to maximise the expected total profit. Finally, a series of simulation experiments are conducted to reveal the impact of some key factors, and the experiment results provide theoretical guidance and implementation methods for companies to maximise overall profits.