Random Key Self-Organizing Migrating Algorithm for Permutation Problems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F19%3A10244290" target="_blank" >RIV/61989100:27240/19:10244290 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/8790322" target="_blank" >https://ieeexplore.ieee.org/document/8790322</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CEC.2019.8790322" target="_blank" >10.1109/CEC.2019.8790322</a>
Alternative languages
Result language
angličtina
Original language name
Random Key Self-Organizing Migrating Algorithm for Permutation Problems
Original language description
Self-organizing migrating algorithm (SOMA) is a modern stochastic optimization algorithm. It is built upon the principles of evolutionary and swarm computation and has been successfully applied to a variety of theoretical and practical optimization problems. The candidate solutions in SOMA are real-valued and the use of the algorithm for continuous optimization is straightforward. Its application to combinatorial optimization, on the other hand, requires a translation of candidate solutions from continuous search space to discrete problem solution space. In this work, a version of SOMA suitable for permutation problems is proposed and evaluated on two well-known hard permutation problems.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10200 - Computer and information sciences
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings
ISBN
978-1-72812-153-6
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
2878-2885
Publisher name
IEEE
Place of publication
Piscataway
Event location
Wellington
Event date
Jun 10, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000502087102115