Interaction Potentials and Glass Formation: A Survey of Computer Experiments

2007 ◽  
pp. 397-453 ◽  
Author(s):  
C. A. Angell ◽  
J. H. R. Clarke ◽  
L. V. Woodcock
1990 ◽  
Vol 51 (C4) ◽  
pp. C4-111-C4-117 ◽  
Author(s):  
L. J. GALLEGO ◽  
J. A. SOMOZA ◽  
H. M. FERNANDEZ ◽  
J. A. ALONSO

2015 ◽  
Vol 15 (8) ◽  
pp. 761-766 ◽  
Author(s):  
Feng Chen ◽  
Zhe-Yi Hu ◽  
Wei-Wei Jia ◽  
Jing-Tao Lu ◽  
Yuan-Sheng Zhao

1995 ◽  
Vol 185 (1-2) ◽  
pp. 151-158 ◽  
Author(s):  
Miroslav Jamnický ◽  
Peter Znášik ◽  
Daniel Tunega ◽  
Malcolm D. Ingram
Keyword(s):  

Author(s):  
Andrei M. Bandalouski ◽  
Natalja G. Egorova ◽  
Mikhail Y. Kovalyov ◽  
Erwin Pesch ◽  
S. Armagan Tarim

AbstractIn this paper we present a novel approach to the dynamic pricing problem for hotel businesses. It includes disaggregation of the demand into several categories, forecasting, elastic demand simulation, and a mathematical programming model with concave quadratic objective function and linear constraints for dynamic price optimization. The approach is computationally efficient and easy to implement. In computer experiments with a hotel data set, the hotel revenue is increased by about 6% on average in comparison with the actual revenue gained in a past period, where the fixed price policy was employed, subject to an assumption that the demand can deviate from the suggested elastic model. The approach and the developed software can be a useful tool for small hotels recovering from the economic consequences of the COVID-19 pandemic.


2021 ◽  
pp. 116387
Author(s):  
L.A. Padilla ◽  
A. Ramírez-Hernández ◽  
J. Quintana-H ◽  
A.L. Benavides ◽  
J.C. Armas-Perez

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