A simple semi on-line algorithm for P2//Cmax with a buffer
Information Processing Letters
The Power of Reordering for Online Minimum Makespan Scheduling
FOCS '08 Proceedings of the 2008 49th Annual IEEE Symposium on Foundations of Computer Science
Online scheduling on two uniform machines to minimize the makespan
Theoretical Computer Science
Online scheduling with reassignment on two uniform machines
Theoretical Computer Science
AAIM'10 Proceedings of the 6th international conference on Algorithmic aspects in information and management
Online scheduling with rearrangement on two related machines
Theoretical Computer Science
Optimal algorithms for online scheduling with bounded rearrangement at the end
Theoretical Computer Science
Online scheduling with reassignment
Operations Research Letters
Online and semi-online scheduling of two machines under a grade of service provision
Operations Research Letters
Semi on-line algorithms for the partition problem
Operations Research Letters
Online scheduling with one rearrangement at the end: Revisited
Information Processing Letters
Online minimum makespan scheduling with a buffer
FAW-AAIM'12 Proceedings of the 6th international Frontiers in Algorithmics, and Proceedings of the 8th international conference on Algorithmic Aspects in Information and Management
Semi-online scheduling with two GoS levels and unit processing time
Theoretical Computer Science
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In this paper, we consider semi-online hierarchical scheduling problems on two identical machines, with the purpose of minimizing the makespan. The first investigated problem is the buffer version, where a buffer of a fixed capacity K is available for storing at most K jobs. When the current job is given, we are allowed to assign it on some machine irrecoverably; or temporarily store it in the buffer. But in the latter case if the buffer was full then an earlier job is removed from the buffer and assigned it to some machine. The second one is a reassignment version, where when the input is end, we are allowed to reassign at most K jobs. For both versions, we show no online algorithm can have a competitive ratio less than 32, then propose two online algorithms with a competitive ratio 32 with K=1 for both versions of the problem, i.e., using only buffer of size one, or using only one rearrangement at the end.