Progressive Archive in Adaptive jSO Algorithm

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F24%3AA25038AE" target="_blank" >RIV/61988987:17310/24:A25038AE - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/2227-7390/12/16/2534" target="_blank" >https://www.mdpi.com/2227-7390/12/16/2534</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/math12162534" target="_blank" >10.3390/math12162534</a>

Result language

angličtina

Original language name

Progressive Archive in Adaptive jSO Algorithm

Original language description

The problem of optimisation methods is the stagnation of population P, which results in a local solution for the task. This problem can be solved by employing an archive for good historical solutions outperformed by the new better offspring. The archive A was introduced with the variant of adaptive differential evolution (DE), and it was successfully applied in many adaptive DE variants including the efficient jSO algorithm. In the original jSO, the historical good individuals replace the random existing positions in A. It causes that outperformed historical solution from P with lower quality to replace the stored solution in A with better quality. In this paper, a new approach to replace individuals in archive A more progressively is proposed. Outperformed individuals from P replace solutions in the worse part of A based on the function value. The portion of A selected for replacement is controlled by the input parameter, and its setting is studied in this experiment. The proposed progressive archive is employed in the original jSO. Moreover, the Eigenvector transformation of the individuals for crossover is applied to increase the efficiency for the rotated optimisation problems. The efficiency of the proposed progressive archive and the Eigen crossover are evaluated using the set of 29 optimisation problems for CEC 2024 and various dimensionality. All the experiments were performed on a standard PC, and the results were compared using the standard statistical methods. The newly proposed algorithm with the progressive archive approach performs substantially better than the original jSO, especially when 20 or 40% of the worse individuals of A are set for replacement. The Eigen crossover increases the performance of the proposed jSO algorithm with the progressive archive approach. The estimated time complexity illustrates the low computational demands of the proposed archive approach.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10102 - Applied mathematics

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Mathematics

ISSN

2227-7390

e-ISSN

2227-7390

Volume of the periodical

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Issue of the periodical within the volume

16

Country of publishing house

CH - SWITZERLAND

Number of pages

20

Pages from-to

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UT code for WoS article

001306012300001

EID of the result in the Scopus database

2-s2.0-85202618174