Discretization Of Decision Variables In Optimization Algorithms

Loading...
Thumbnail Image
Date
2018
ORCID
Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract
This paper presents a verification of universal method for discretization of decision space in optimization algorithms. Real-world optimization tasks frequently use discontinuous decision variables and in order to effectively optimize such tasks, it is necessary to exploit an optimization algorithm that meets such requirement. Unfortunately, very few evolutionary algorithms can naturally work with discontinuous decision space. The method that entitles all optimization algorithms to effectively solve problems with discrete variables is here described and experimentally verified.
Description
Citation
Proceedings of the 24th Conference STUDENT EEICT 2018. s. 307-311. ISBN 978-80-214-5614-3
http://www.feec.vutbr.cz/EEICT/
Document type
Peer-reviewed
Document version
Published version
Date of access to the full text
Language of document
en
Study field
Comittee
Date of acceptance
Defence
Result of defence
Document licence
© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
DOI
Citace PRO