Deciding Stability in Packet-Switched FIFO Networks Under the Adversarial Queuing Model in Polynomial Time,

2005 ◽  
pp. 429-441 ◽  
Author(s):  
Maria J. Blesa
Keyword(s):  
Polynomial Time ◽  
Queuing Model ◽  
Adversarial Queuing

A Characterization of Universal Stability in the Adversarial Queuing Model

2004 ◽  
Vol 34 (1) ◽  
pp. 41-66 ◽  
Author(s):  
Carme Àlvarez ◽  
Maria Blesa ◽  
Maria Serna
Keyword(s):  
Queuing Model ◽  
Adversarial Queuing ◽  
Universal Stability

Stability Behavior of FIFO Protocol in the Adversarial Queuing Model

2003 ◽  
pp. 464-479 ◽  
Author(s):  
Dimitrios K. Koukopoulos ◽  
Sotiris E. Nikoletseas ◽  
Paul G. Spirakis
Keyword(s):  
Queuing Model ◽  
Stability Behavior ◽  
Adversarial Queuing

The 2-closure of a 32-transitive group in polynomial time

2018 ◽  
Vol 60 (2) ◽  
pp. 360-375
Author(s):  
A. V. Vasil'ev ◽  
D. V. Churikov
Keyword(s):  
Polynomial Time ◽  
Transitive Group

Queuing Model Based Data Centers: A Review

2019 ◽  
Vol 123 ◽  
pp. 11-20 ◽  
Author(s):  
N. Thirupathi Rao ◽  
Debnath Bhattacharyya ◽  
S. Naga Mallik Raj
Keyword(s):  
Data Centers ◽  
Queuing Model ◽  
Model Based

Learning Importance of Preferences

10.29007/v68w ◽  
2018 ◽  
Author(s):  
Ying Zhu ◽  
Mirek Truszczynski
Keyword(s):  
Polynomial Time ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Scoring Rules ◽  
Np Hard ◽  
Individual Preferences

We study the problem of learning the importance of preferences in preference profiles in two important cases: when individual preferences are aggregated by the ranked Pareto rule, and when they are aggregated by positional scoring rules. For the ranked Pareto rule, we provide a polynomial-time algorithm that finds a ranking of preferences such that the ranked profile correctly decides all the examples, whenever such a ranking exists. We also show that the problem to learn a ranking maximizing the number of correctly decided examples (also under the ranked Pareto rule) is NP-hard. We obtain similar results for the case of weighted profiles when positional scoring rules are used for aggregation.

Optimalisasi Pekerjaan Pemindahan Tanah Pada Proyek Embung Begawan Kota Tarakan Dengan Model Antrian

2017 ◽  
Vol 1 (2) ◽  
pp. 75
Author(s):  
Budi Setiawan ◽  
Hermanto Hermanto
Keyword(s):  
Soil Removal ◽  
Production Capacity ◽  
Optimal Time ◽  
Dump Truck ◽  
Queuing Model ◽  
Soil Movement ◽  
Transportation Equipment ◽  
Model Method ◽  
Mechanical Devices ◽  
Time Required

The Embung Bengawan Project in Tarakan City has several jobs requiring heavy equipment including mechanical soil removal activities. Activity of mechanical soil movement is a series in work of loading and transportation equipment. In order to achieve optimal mechanical soil removal targets, it is necessary to know the performance of the machine during the mechanical soil removal process. The optimization of production is the way to obtain production that is in accordance with optimal conditions of mechanical devices. This paper discusses the optimization of dump truck queue time and the number of dump trucks. Performance calculation tool using the method of production capacity of the tool, and calculate the optimal queue using the Queue Model method. Calculation using queuing model method obtained by result of time required by 3 excavator unit and with combined amount of dump truck will give result of cost equal to Rp 48,097,711 / day, and dump truck waiting time in queue to 1 minute. Then the optimal time is obtained by operating 3 units of excavators with a cost difference of Rp 3,572,826 / day from the real condition of the field that operates 2 excavator units

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