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International Symposium on Parallel Computing in Electrical Engineering (PARELEC'06)
Parallelisation of Genetic Algorithms for Solving University Timetabling Problems
Bialystok, Poland
September 13-September 17
ISBN: 0-7695-2554-7
ASCII Text
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Karol Banczyk, Tomasz Boinski, Henryk Krawczyk, "Parallelisation of Genetic Algorithms for Solving University Timetabling Problems," Parallel Computing in Electrical Engineering, International Conference on, pp. 325-330, International Symposium on Parallel Computing in Electrical Engineering (PARELEC'06), 2006.
 
 
BibTex
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@article{ 10.1109/PARELEC.2006.64,
author = {Karol Banczyk and Tomasz Boinski and Henryk Krawczyk},
title = {Parallelisation of Genetic Algorithms for Solving University Timetabling Problems},
journal ={Parallel Computing in Electrical Engineering, International Conference on},
volume = {0},
year = {2006},
isbn = {0-7695-2554-7},
pages = {325-330},
doi = {http://doi.ieeecomputersociety.org/10.1109/PARELEC.2006.64},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Parallel Computing in Electrical Engineering, International Conference on
TI - Parallelisation of Genetic Algorithms for Solving University Timetabling Problems
SN - 0-7695-2554-7
SP325
EP330
A1 - Karol Banczyk,
A1 - Tomasz Boinski,
A1 - Henryk Krawczyk,
PY - 2006
KW - null
VL - 0
JA - Parallel Computing in Electrical Engineering, International Conference on
ER -
 
Karol Banczyk, Gdansk University of Technology, Poland
Tomasz Boinski, Gdansk University of Technology, Poland
Henryk Krawczyk, Gdansk University of Technology, Poland
Genetic algorithms play an important role in solving many optimisation problems. The paper concentrates on the design of a parallel genetic algorithm for obtaining acceptable and possibly good university timetables. Some known parallelisation techniques are introduced and the chosen implementation using MPI platform is shown. The masterslave management structure is assumed and the system scalability and the solution quality as function of the processing node number and population size are estimated.
Citation:
Karol Banczyk, Tomasz Boinski, Henryk Krawczyk, "Parallelisation of Genetic Algorithms for Solving University Timetabling Problems," parelec, pp.325-330, International Symposium on Parallel Computing in Electrical Engineering (PARELEC'06), 2006
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