A Pareto Front Numerical Reconstruction Strategy Applied to a Satellite System Conceptual Design

Gustavo J. Santos (), Sebastián M. Giusti () and Roberto Alonso ()
Additional contact information
Gustavo J. Santos: Unidad de Formación Superior CONAE – Universidad Tecnológica Nacional
Sebastián M. Giusti: Maestro M. López esq. Cruz Roja Argentina
Roberto Alonso: Falda del Cañete

A chapter in Modeling and Optimization in Space Engineering, 2023, pp 331-348 from Springer

Abstract: Abstract A satellite system conceptual design problem is addressed in this work. A multi-objective parametric optimization problem is formulated and efficiently solved. The objectives considered are usually opposed among them, such as performance, mass, budget, and volume. By solving the optimization problem, a minimum set of different satellite configurations is obtained. Therefore, the decision-maker can select the best one, knowing that each one fulfills the requirements suite. The strategy developed in this work is based on the direct numerical simulation (DNS) of the optimization problem. The optimal Pareto front is obtained in a numerical setting. This new tool can optimize the complete system as a whole. Usually, in the standard engineering procedure, each of the interdisciplinary groups performs the optimization of their subsystem. After that, the optimized system is obtained by overlapping all of these individually optimized parts. Clearly, this standard procedure only can create a sub-optimal design. With the approach presented here the global optimal solution is guaranteed. The strategy is applied to a low orbit satellite model and a comparison with a genetic algorithm-based multi-objective optimization procedure is also presented.

Keywords: Global optimisation; Interpolation; Q-law; Estimation of distribution algorithms; Evolutionary approach (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-031-24812-2_12

Ordering information: This item can be ordered from
http://www.springer.com/9783031248122

DOI: 10.1007/978-3-031-24812-2_12

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().