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

1993 ◽  
Vol 31 (12) ◽  
pp. 2817-2834 ◽  
Author(s):  
A. C. KAPLAN ◽  
A. T. UNAL
2014 ◽  
Vol 22 (1) ◽  
pp. 105-138 ◽  
Author(s):  
Su Nguyen ◽  
Mengjie Zhang ◽  
Mark Johnston ◽  
Kay Chen Tan

Due-date assignment plays an important role in scheduling systems and strongly influences the delivery performance of job shops. Because of the stochastic and dynamic nature of job shops, the development of general due-date assignment models (DDAMs) is complicated. In this study, two genetic programming (GP) methods are proposed to evolve DDAMs for job shop environments. The experimental results show that the evolved DDAMs can make more accurate estimates than other existing dynamic DDAMs with promising reusability. In addition, the evolved operation-based DDAMs show better performance than the evolved DDAMs employing aggregate information of jobs and machines.


2008 ◽  
Vol 187 (1) ◽  
pp. 31-45 ◽  
Author(s):  
Adil Baykasoğlu ◽  
Mustafa Göçken ◽  
Zeynep D. Unutmaz

1993 ◽  
Vol 68 (2) ◽  
pp. 212-227 ◽  
Author(s):  
Nabil R. Adam ◽  
J.Will M. Bertrand ◽  
Diane C. Morehead ◽  
Julius Surkis

2018 ◽  
Vol 65 (5) ◽  
pp. 393-409 ◽  
Author(s):  
Yunqiang Yin ◽  
Yongjian Yang ◽  
Dujuan Wang ◽  
T.C.E. Cheng ◽  
Chin-Chia Wu

Sign in / Sign up

Export Citation Format

Share Document