Parallel Bivariate Marginal Distribution Algorithm with Probability Model Migration

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F08%3APU76810" target="_blank" >RIV/00216305:26230/08:PU76810 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Parallel Bivariate Marginal Distribution Algorithm with Probability Model Migration
Original language description
This chapter presents a new concept of parallel Bivariate Marginal Distribution Algorithm (BMDA) using the stepping stone communication model with the unidirectional ring topology. The traditional migration of individuals is compared with a newly proposed technique of probability model migration. The idea of the new adaptive BMDA (aBMDA) algorithms is to modify the classic learning of the probability model (applied in the sequential BMDA). In the proposed strategy, the adap-tive learning of the residentprobability model is used. The evaluation of pair dependency, using Pearson's chi-square statistics is influenced by the relevant immigrant pair dependency according to the quality of resident and immigrant subpopulation. Experimental results show thatthe proposed aBMDA significantly outperforms the traditional concept of migration of individuals.
Czech name
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Czech description
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Project
<a href="/en/project/GA102%2F07%2F0850" target="_blank" >GA102/07/0850: Design and hardware implementation of a patent-invention machine</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2008
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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