Explaining SOMA: The relation of stochastic perturbation to population diversity and parameter space coverage

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F21%3A63544458" target="_blank" >RIV/70883521:28140/21:63544458 - isvavai.cz</a>

Výsledek na webu

<a href="https://dl.acm.org/doi/pdf/10.1145/3449726.3463211" target="_blank" >https://dl.acm.org/doi/pdf/10.1145/3449726.3463211</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3449726.3463211" target="_blank" >10.1145/3449726.3463211</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Explaining SOMA: The relation of stochastic perturbation to population diversity and parameter space coverage

Popis výsledku v původním jazyce

The Self-Organizing Migrating Algorithm (SOMA) is enjoying a renewed interest of the research community, following recent achievements in various application areas and renowned performance competitions. In this paper, we focus on the importance and effect of the perturbation operator in SOMA as the perturbation is one of the fundamental inner principles of SOMA. In this in-depth study, we present data, visualizations, and analysis of the effect of the perturbation on the population, its diversity and average movement patterns. We provide evidence that there is a direct relation between the perturbation intensity (set by control parameter prt) and the rate of diversity loss. The perturbation setting further affects the exploratory ability of the algorithm, as is demonstrated here by analysing the parameter space coverage of the population. We aim to provide insight and explanation of the impact of perturbation in SOMA for future researchers and practitioners. © 2021 ACM.

Název v anglickém jazyce

Explaining SOMA: The relation of stochastic perturbation to population diversity and parameter space coverage

Popis výsledku anglicky

The Self-Organizing Migrating Algorithm (SOMA) is enjoying a renewed interest of the research community, following recent achievements in various application areas and renowned performance competitions. In this paper, we focus on the importance and effect of the perturbation operator in SOMA as the perturbation is one of the fundamental inner principles of SOMA. In this in-depth study, we present data, visualizations, and analysis of the effect of the perturbation on the population, its diversity and average movement patterns. We provide evidence that there is a direct relation between the perturbation intensity (set by control parameter prt) and the rate of diversity loss. The perturbation setting further affects the exploratory ability of the algorithm, as is demonstrated here by analysing the parameter space coverage of the population. We aim to provide insight and explanation of the impact of perturbation in SOMA for future researchers and practitioners. © 2021 ACM.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název statě ve sborníku

GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion

ISBN

978-145038351-6

ISSN

—

e-ISSN

—

Počet stran výsledku

9

Strana od-do

1944-1952

Název nakladatele

Association for Computing Machinery

Místo vydání

New York

Místo konání akce

Lille

Datum konání akce

10. 7. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—