hierarchical machines
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Author(s):  
Omer Nguena Timo ◽  
Alexandre Petrenko ◽  
Arnaud Dury ◽  
S. Ramesh


2014 ◽  
Vol 531 ◽  
pp. 37-46 ◽  
Author(s):  
Yong Wu ◽  
T.C.E. Cheng ◽  
Min Ji


2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Li Luo ◽  
Chun-rong Qin ◽  
Shi-jun Tang ◽  
Xian Chen ◽  
Hui-li Guo

From the on-line point, we consider the hospital’s medical examination appointment problem with hierarchical machines. This approach eliminates the need for both demand forecasts and a risk-neutrality assumption. Due to different unit revenue, uncertain demand, and arrival of patients, we design on-line booking policies for two kinds of different situations from the perspective of on-line policy and competitive analysis. After that, we prove the optimal competitive ratios. Through numerical examples, we compare advantages and disadvantages between on-line policies and traditional policies, finding that there is different superiority for these two policies under different arrival sequences.



2013 ◽  
Vol 29 (4) ◽  
pp. 781-795 ◽  
Author(s):  
An Zhang ◽  
Yiwei Jiang ◽  
Lidan Fan ◽  
Jueliang Hu


2012 ◽  
Vol 04 (01) ◽  
pp. 1250012
Author(s):  
YIWEI JIANG ◽  
AN ZHANG ◽  
JUELIANG HU

This paper investigates an online hierarchical scheduling problem with resource augmentation, i.e., the resources of the online algorithms are different from those of the offline algorithms. The machines are provided with different capacity according to their hierarchies. One with the hierarchy 1 has a speed of s(q) in the online (offline) algorithms and can process all the jobs. The other with hierarchy 2 has a speed of 1 in the online/offline algorithms and can only process partial jobs. The objective is to minimize makespan. For any 0 < q, s < ∞, we present optimal online algorithms with parametric competitive ratios.



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