Uniform parallel machine scheduling problems with fixed machine cost

2016 ◽  
Vol 12 (1) ◽  
pp. 73-86 ◽  
Author(s):  
Kai Li ◽  
Hui-Juan Zhang ◽  
Ba-Yi Cheng ◽  
Panos M. Pardalos
Keyword(s):  
Machine Scheduling ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Scheduling Problems ◽  
Machine Cost ◽  
Uniform Parallel Machine Scheduling ◽  
Machine Scheduling Problems

Parallel Machine Scheduling Problems

2013 ◽  
pp. 189-215
Author(s):  
Alessandro Agnetis ◽  
Jean-Charles Billaut ◽  
Stanisław Gawiejnowicz ◽  
Dario Pacciarelli ◽  
Ameur Soukhal
Keyword(s):  
Machine Scheduling ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Scheduling Problems ◽  
Machine Scheduling Problems

scholarly journals Two Parallel-Machine Scheduling Problems with Function Constraint

2020 ◽  
Vol 2020 ◽  
pp. 1-6 ◽  
Author(s):  
Chia-Lun Hsu ◽  
Jan-Ray Liao
Keyword(s):  
Completion Time ◽  
Machine Scheduling ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Total Completion Time ◽  
Scheduling Problems ◽  
Worst Case ◽  
Time Problem ◽  
Constraint Problem ◽  
Machine Scheduling Problems

The objective of this paper is to minimize both the makespan and the total completion time. Since parallel-machine scheduling which contains the function constraint problem has been a new issue, this paper explored two parallel-machine scheduling problems with function constraint, which refers to the situation that the two machines have a same function but one of the machines has another. We pointed out that the function constraint occurs not only in the manufacturing system but also in the service system. For the makespan problem, we demonstrated that it is NP-hard in the ordinary sense. In addition, we presented a polynomial time heuristic for this problem and have proved its worst-case ratio is not greater than 5/4. Furthermore, we simulated the performance of the algorithm through computational testing. The overall mean percent error of the heuristic is 0.0565%. The results revealed that the proposed algorithm is quite efficient. For the total completion time problem, we have proved that it can be solved in On4 time.

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