scholarly journals Simulation and Comparison Analysis of Due Date Assignment Methods Using Scheduling Rules in a Job Shop Production System

Author(s):  
Fitsum Getachew ◽  
Eshetie Berhan
2021 ◽  
Vol 1 (2) ◽  
pp. 46-51
Author(s):  
Dwi Ayu Lestari, Vikha Indira Asri

Scheduling is defined as the process of sequencing the manufacture of a product as a whole on several machines. All industries need proper scheduling to manage the allocation of resources so that the production system can run quickly and precisely as of it can produce optimal product. PT. Sari Warna Asli Unit V is one of the companies that implements a make to order production system with the FCFS system. Thus, scheduling the production process at this company is also known as job shop production scheduling. The methods used in this research are the CDS method, the EDD method and the FCFS method. The purpose of this research is to minimize the production time and determine the best method that can be applied to the company. The results of this research showed that the makespan obtained in the company's scheduling system with FCFS rules was 458 minutes, and the results of scheduling using the CDS method obtained a makespan value of 329 minutes, then the best production scheduling method that had the smallest makespan value was the CDS method.


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.


1989 ◽  
Vol 21 (2) ◽  
pp. 153-161 ◽  
Author(s):  
TIMOTHY D. FRY ◽  
PATRICK R. PHILIPOOM ◽  
ROBERT E. MARKLAND

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