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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.

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