SAGA: A Combination of Genetic and Simulated Annealing Algorithms for Physical Data Warehouse Design

2006 ◽  
pp. 212-219 ◽  
Author(s):  
Ladjel Bellatreche ◽  
Kamel Boukhalfa ◽  
Hassan Ismail Abdalla
Keyword(s):  
Simulated Annealing ◽  
Data Warehouse ◽  
Physical Data ◽  
Warehouse Design ◽  
Annealing Algorithms

Physical Data Warehouse Design

2014 ◽  
pp. 233-284
Author(s):  
Alejandro Vaisman ◽  
Esteban Zimányi
Keyword(s):  
Data Warehouse ◽  
Physical Data ◽  
Warehouse Design

Physical Data Warehouse Design

2016 ◽  
pp. 195-228
Author(s):  
Daniel Linstedt ◽  
Michael Olschimke
Keyword(s):  
Data Warehouse ◽  
Physical Data ◽  
Warehouse Design

scholarly journals Physical Data Warehouse Design Using Neural Network

2010 ◽  
Vol 1 (3) ◽  
pp. 99-107 ◽  
Author(s):  
Mayank Sharma ◽  
Navin Rajpal ◽  
B.V.R. Reddy
Keyword(s):  
Neural Network ◽  
Data Warehouse ◽  
Physical Data ◽  
Warehouse Design

scholarly journals A simulated annealing-based algorithm for selecting balanced samples

2021 ◽  
Author(s):  
Roberto Benedetti ◽  
Maria Michela Dickson ◽  
Giuseppe Espa ◽  
Francesco Pantalone ◽  
Federica Piersimoni
Keyword(s):  
Simulated Annealing ◽  
Optimization Problem ◽  
Sample Selection ◽  
Auxiliary Information ◽  
Real Data ◽  
Simulation Experiments ◽  
Balanced Sampling ◽  
Inclusion Probabilities ◽  
Random Method ◽  
Annealing Algorithms

AbstractBalanced sampling is a random method for sample selection, the use of which is preferable when auxiliary information is available for all units of a population. However, implementing balanced sampling can be a challenging task, and this is due in part to the computational efforts required and the necessity to respect balancing constraints and inclusion probabilities. In the present paper, a new algorithm for selecting balanced samples is proposed. This method is inspired by simulated annealing algorithms, as a balanced sample selection can be interpreted as an optimization problem. A set of simulation experiments and an example using real data shows the efficiency and the accuracy of the proposed algorithm.

Optimization of physical data tables by simulated annealing

1989 ◽  
Vol 3 (3) ◽  
pp. 33 ◽  
Author(s):  
Ellen M. Corey ◽  
David A. Young
Keyword(s):  
Simulated Annealing ◽  
Physical Data ◽  
Data Tables
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