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Digital Library of the
European Council for Modelling and Simulation |
Title: |
Efficiency
Of Memetic And Evolutionary Computing In
Combinatorial Optimisation |
Authors: |
Magdalena Kolybacz,
Michal Kowol, Lukasz Lesniak,
Aleksander Byrski, Marek Kisiel-Dorohinicki |
Published in: |
(2013).ECMS 2013 Proceedings edited
by: W. Rekdalsbakken, R. T. Bye, H. Zhang European Council for Modeling
and Simulation. doi:10.7148/2013 ISBN:
978-0-9564944-6-7 27th
European Conference on Modelling and Simulation, Aalesund, Norway, May 27th –
30th, 2013 |
Citation
format: |
Magdalena
Kolybacz, Michal Kowol,
Lukasz Lesniak, Aleksander
Byrski, Marek Kisiel-Dorohinicki (2013). Efficiency Of Memetic And Evolutionary Computing In Combinatorial Optimisation, ECMS 2013 Proceedings edited
by: W. Rekdalsbakken, R. T. Bye, H. Zhang, European Council for Modeling
and Simulation. doi:10.7148/2013-0525 |
DOI: |
http://dx.doi.org/10.7148/2013-0525 |
Abstract: |
Difficult search and optimisation problems call for complex techniques for
solving them. In particular, in cases when fitness function is costly,
applying solutions, such as agent-based computing systems may be fruitful.
This approach may yield even better results, in the case of memetic computing, as these algorithms tend to
significantly increase the number of fitness function calls, because of their
nature. This paper may be treated as a milestone in preparing to tackle
combinatorial optimisation problems with memetic approaches in agent-based systems. After
discussing the selected problems and details of population-oriented
meta-heuristics to solve them, experimental results (with stress put on
efficiency) are presented. Then details of applying EMAS-class systems are
given and, in the end, preliminary EMAS results obtained for combinatorial optimisation
are shown and the work is concluded. |
Full
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