Adaptive population techniques in Evolution Algorithms
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24210%2F19%3A00006778" target="_blank" >RIV/46747885:24210/19:00006778 - isvavai.cz</a>
Result on the web
<a href="http://mme2019.ef.jcu.cz/files/conference_proceedings.pdf" target="_blank" >http://mme2019.ef.jcu.cz/files/conference_proceedings.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Adaptive population techniques in Evolution Algorithms
Original language description
Evolution algorithms are one of the most popular optimization techniques for its ability to solve wide field of general combinatorial problems. They are simple to implement and use as its mechanisms are logical and untestable due to its natural and common sense. However its optimization results as well as timespan are heavy dependent on setting searching parameters as crossover, mutation rates, population size etc. Setting those parameters requires intuition and experience and is also beneficial to change them during optimization as necessity to exploit and explore changes during optimization. Those are the reasons why nowadays research in the field of Evolutionary Computing is focusing more and more on the adaptive operator control. This article is focusing on part of adaptive parameter control which is known not only as responsible for quality of results but also for optimization time. The research is focusing on population sizing schemes together with selection and elimination procedures. It is reviewing known techniques and presenting original solution. Those techniques are then tested on known theoretical job shop scheduling problems and their efficiency is discussed. This paper was written with aid of students (Vignesh Babu Kuduva Gopinath and Jiří Bareš).
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
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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
37th International Conference on Mathematical Methods in Economics 2019
ISBN
978-80-7394-760-6
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
67-72
Publisher name
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Place of publication
České Budějovice
Event location
České Budějovice
Event date
Jan 1, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000507570400010