Job Shop Scheduling: Is Manual Application of Dispatching Rules Feasible?

1975 ◽  
Vol 26 (1) ◽  
pp. 35
Author(s):  
C. C. New
2000 ◽  
Vol 11 (1) ◽  
pp. 73-81 ◽  
Author(s):  
V. Subramaniam ◽  
G. K. Lee ◽  
G. S. Hong ◽  
Y. S. Wong ◽  
T. Ramesh

2019 ◽  
Vol 18 (01) ◽  
pp. 35-56
Author(s):  
M. Habib Zahmani ◽  
B. Atmani

Identifying the best Dispatching Rule in order to minimize makespan in a Job Shop Scheduling Problem is a complex task, since no Dispatching Rule is better than all others in different scenarios, making the selection of a most effective rule which is time-consuming and costly. In this paper, a novel approach combining Data Mining, Simulation, and Dispatching Rules is proposed. The aim is to assign in real-time a set of Dispatching Rules to the machines on the shop floor while minimizing makespan. Experiments show that the suggested approach is effective and reduces the makespan within a range of 1–44%. Furthermore, this approach also reduces the required computation time by using Data Mining to determine and assign the best Dispatching Rules to machines.


Processes ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1398
Author(s):  
Jae-Gon Kim ◽  
Hong-Bae Jun ◽  
June-Young Bang ◽  
Jong-Ho Shin ◽  
Seong-Hoon Choi

In many manufacturing or service industries, there exists maximum allowable tardiness for orders, according to purchase contracts between the customers and suppliers. Customers may cancel their orders and request compensation for damages, for breach of contract, when the delivery time is expected to exceed maximum allowable tardiness, whereas they may accept the delayed delivery of orders with a reasonable discount of price within maximum allowable tardiness. Although many research works have been produced on the job shop scheduling problem relating to minimizing total tardiness, none of them have yet considered problems with maximum allowable tardiness. In this study, we solve a job shop scheduling problem under maximum allowable tardiness, with the objective of minimizing tardiness penalty costs. Two kinds of penalty costs are considered, i.e., one for tardy jobs, and the other for canceled jobs. To deal with this problem within a reasonable time at actual production facilities, we propose several dispatching rules by extending well-known dispatching rules for the job shop scheduling problem, in cooperation with a probabilistic conception of those rules. To evaluate the proposed rules, computational experiments were carried out on 300 test instances. The test results show that the suggested probabilistic dispatching rules work better than the existing rules and the optimization solver CPLEX, with a time limit.


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