Multi-Objective PSO with Variable Number of Dimensions for Space Robot Path Optimization
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F23%3APU148364" target="_blank" >RIV/00216305:26220/23:PU148364 - isvavai.cz</a>
Výsledek na webu
<a href="https://www.mdpi.com/1999-4893/16/6/307/htm" target="_blank" >https://www.mdpi.com/1999-4893/16/6/307/htm</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/a16060307" target="_blank" >10.3390/a16060307</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Multi-Objective PSO with Variable Number of Dimensions for Space Robot Path Optimization
Popis výsledku v původním jazyce
This paper aims to solve the space robot pathfinding problem, formulated as a multi-objective (MO) optimization problem with a variable number of dimensions (VND). This formulation enables the search and comparison of potential solutions with different model complexities within a single optimization run. A novel VND MO algorithm based on the well-known particle swarm optimization (PSO) algorithm is introduced and thoroughly described in this paper. The novel VNDMOPSO algorithm is validated on a set of 21 benchmark problems with different dimensionality settings and compared with two other state-of-the-art VND MO algorithms. Then, it is applied to solve five different instances of the space robot pathfinding problem formulated as a VND MO problem where two objectives are considered: (1) the minimal distance of the selected path, and (2) the minimal energy cost (expressed as the number of turning points). VNDMOPSO shows at least comparable or better convergence on the benchmark problems and significantly better convergence properties on the VND pathfinding problems compared with other VND MO algorithms.
Název v anglickém jazyce
Multi-Objective PSO with Variable Number of Dimensions for Space Robot Path Optimization
Popis výsledku anglicky
This paper aims to solve the space robot pathfinding problem, formulated as a multi-objective (MO) optimization problem with a variable number of dimensions (VND). This formulation enables the search and comparison of potential solutions with different model complexities within a single optimization run. A novel VND MO algorithm based on the well-known particle swarm optimization (PSO) algorithm is introduced and thoroughly described in this paper. The novel VNDMOPSO algorithm is validated on a set of 21 benchmark problems with different dimensionality settings and compared with two other state-of-the-art VND MO algorithms. Then, it is applied to solve five different instances of the space robot pathfinding problem formulated as a VND MO problem where two objectives are considered: (1) the minimal distance of the selected path, and (2) the minimal energy cost (expressed as the number of turning points). VNDMOPSO shows at least comparable or better convergence on the benchmark problems and significantly better convergence properties on the VND pathfinding problems compared with other VND MO algorithms.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
20204 - Robotics and automatic control
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2023
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Algorithms
ISSN
1999-4893
e-ISSN
—
Svazek periodika
16
Číslo periodika v rámci svazku
6
Stát vydavatele periodika
CH - Švýcarská konfederace
Počet stran výsledku
20
Strana od-do
1-20
Kód UT WoS článku
001013798800001
EID výsledku v databázi Scopus
2-s2.0-85163718097