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A Computational Approach to TSP Performance Prediction Using Data Mining
Niagara Falls, Ontario, Canada May 21-May 23
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AINAW.2007.1321st International Conference on Adva ...
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Paula Cecilia Fritzsche, Dolores Rexachs, Emilio Luque, "A Computational Approach to TSP Performance Prediction Using Data Mining," Advanced Information Networking and Applications Workshops, International Conference on, vol. 1, pp. 252-259, 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07), 2007.
 
 
BibTex
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@article{ 10.1109/AINAW.2007.13,
author = {Paula Cecilia Fritzsche and Dolores Rexachs and Emilio Luque},
title = {A Computational Approach to TSP Performance Prediction Using Data Mining},
journal ={Advanced Information Networking and Applications Workshops, International Conference on},
volume = {1},
year = {2007},
isbn = {0-7695-2847-3},
pages = {252-259},
doi = {http://doi.ieeecomputersociety.org/10.1109/AINAW.2007.13},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Advanced Information Networking and Applications Workshops, International Conference on
TI - A Computational Approach to TSP Performance Prediction Using Data Mining
SN - 0-7695-2847-3
SP252
EP259
A1 - Paula Cecilia Fritzsche,
A1 - Dolores Rexachs,
A1 - Emilio Luque,
PY - 2007
KW - null
VL - 1
JA - Advanced Information Networking and Applications Workshops, International Conference on
ER -
 
Paula Cecilia Fritzsche, University Autonoma of Barcelona, Spain
Dolores Rexachs, University Autonoma of Barcelona, Spain
Emilio Luque, University Autonoma of Barcelona, Spain
The increase in the use of parallel distributed architectures in order to solve large-scale scientific problems has generated the need for performance prediction for both deterministic applications and non-deterministic applications.

The development of a new prediction methodology to estimate the execution time of a hard data-dependent parallel application that solves the traveling salesman problem (TSP) is the primary target of this study. It consists of two big stages: the execution of the TSP algorithms with different input data in order to collect useful data and the application of a data mining procedure through a KDD process.

The approach makes it also possible to evaluate other practical problems that can be formulated as TSP problems.

The experimental results are quite promising, the capacity of prediction is greater than 75%.

Citation:
Paula Cecilia Fritzsche, Dolores Rexachs, Emilio Luque, "A Computational Approach to TSP Performance Prediction Using Data Mining," ainaw, vol. 1, pp.252-259, 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07), 2007
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