Detail publikačního výsledku

Multi-Objective PSO with Variable Number of Dimensions for Space Robot Path Optimization

KADLEC, P.

Originální název

Multi-Objective PSO with Variable Number of Dimensions for Space Robot Path Optimization

Anglický název

Multi-Objective PSO with Variable Number of Dimensions for Space Robot Path Optimization

Druh

Článek WoS

Originální abstrakt

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.

Anglický abstrakt

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.

Klíčová slova

space robot; pathfinding; heuristic algorithm; particle swarm optimization; variable number of dimensions; metameric optimization

Klíčová slova v angličtině

space robot; pathfinding; heuristic algorithm; particle swarm optimization; variable number of dimensions; metameric optimization

Autoři

KADLEC, P.

Rok RIV

2024

Vydáno

20.06.2023

Nakladatel

MDPI

Místo

Basel, Switzerland

ISSN

1999-4893

Periodikum

Algorithms

Svazek

16

Číslo

6

Stát

Švýcarská konfederace

Strany od

1

Strany do

20

Strany počet

20

URL

https://www.mdpi.com/1999-4893/16/6/307/htm

Plný text v Digitální knihovně

http://hdl.handle.net/11012/213599

BibTex

@article{BUT183839,
  author="Petr {Kadlec}",
  title="Multi-Objective PSO with Variable Number of Dimensions for Space Robot Path Optimization",
  journal="Algorithms",
  year="2023",
  volume="16",
  number="6",
  pages="1--20",
  doi="10.3390/a16060307",
  url="https://www.mdpi.com/1999-4893/16/6/307/htm"
}

Dokumenty

algorithms-16-00307-v2