Enhanced Tree-seed Algorithm Solving Real-world Problems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F20%3AA21027CQ" target="_blank" >RIV/61988987:17310/20:A21027CQ - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9311593" target="_blank" >https://ieeexplore.ieee.org/document/9311593</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ISCMI51676.2020.9311593" target="_blank" >10.1109/ISCMI51676.2020.9311593</a>
Alternative languages
Result language
angličtina
Original language name
Enhanced Tree-seed Algorithm Solving Real-world Problems
Original language description
In this paper, an enhanced variant of the efficient nature-inspired Tree-seed optimisation algorithm (TSA) is designed. The original TSA lacks memory of old good solutions and mechanism for rotated objective functions. Two new mechanisms are used to increase the efficiency of the original TS algorithm. At first, archive A for successful seeds is used to help unsuccessful trees (TSrA). Secondly, rotationally invariant Eigenvector transformation of seeds is employed to cope with rotated problems (TSrAeig). Newly proposed TS variants are applied on a set of 22 real-world optimisation problems from CEC 2011. These problems enable to evaluate methods properly for future using in real applications. Results achieved by TSrA and TSrAeig are compared with results of the original TSA algorithm. Newly proposed mechanisms increase the performance of the original TSA algorithm significantly.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2020 7th International Conference on Soft Computing & Machine Intelligence (ISCMI)
ISBN
978-1-7281-7560-7
ISSN
2640-0154
e-ISSN
2640-0146
Number of pages
5
Pages from-to
12-16
Publisher name
IEEE
Place of publication
Stockholm, Sweden
Event location
Stockholm, Sweden
Event date
Nov 13, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—