Optimization and Engineering

, Volume 16, Issue 1, pp 165–181 | Cite as

A multi-objective methodology for spacecraft equipment layouts

  • Ana Paula Curty Cuco
  • Fabiano L. de Sousa
  • Antônio J. Silva Neto


One of the main tasks involving the development of a new spacecraft is how to distribute its electronic equipment over its structural panels. This problem is first addressed in the conception phase of the design and is traditionally carried out by a group of system engineers. It is a multidisciplinary task since structural, thermal, dynamics, and integration issues, must all be taken into account simultaneously. Usually, the initial positioning is done based on the engineers’ experience, followed by an analysis stage (thermal, structural, etc.) in which the design performance and constraints are verified. This process takes time and hence, as soon as a good feasible design is found, it is taken as the baseline. This precludes a broad exploration of the conceptual design space, which usually leads to a suboptimal layout design. In this paper the main features of a multi-objective methodology are presented which were developed to automatically find solutions for a three-dimensional layout of equipment in spacecraft. It includes mass, inertia, thermal and subsystem requirements and geometric constraints using a multi-objective approach that combines CAD and optimization tools in an integrated environment. As a case study, the methodology was applied to the layout optimization of the Brazilian Multi-Mission Space Platform (MMP) equipment. The main results are presented.


Design optimization Layout of satellites Multi-objective optimization 

List of symbols

\( Ang_{XX\_calc} \), \( Ang_{YY\_calc} \), \( Ang_{ZZ\_calc} \) (°, °, °)

Angles between three principal satellite axes of inertia relating to the satellite’s Cartesian coordinate system

\( Ang_{XX\_{\it target}} \), \( Ang_{YY\_{\it target}} \), \( Ang_{ZZ\_{\it target}} \) (°, °, °)

Target angles between three principal satellite axes of inertia relating to the satellite’s Cartesian coordinate system

b (m)

Width of equipment

h (m)

Height of equipment

l (m)

Length of equipment

L (m)

Length of panel


Number of pieces of equipment


Number of panels


Number of cells

P (W)

Thermal power dissipated by equipment

r (m)

Euclidean distance between the center of a piece of equipment and the center of the cell

q (m,m)

Point on a panel coincident to the center of a piece of equipment

Vinter (m3)

Interference volume among pieces of equipment

XCGcalc, YCGcalc, ZCGcalc (m, m, m)

Center of mass coordinates of a layout of the equipment

XCGtarget, YCGtarget, ZCGtarget (m, m, m)

Target center of mass coordinates of a layout of the equipment



Index relative to equipments


Index relative to cells


Index relative to panels


Index relative to objective functions



The authors thank ESSS and ESTECO companies for providing the modeFrontier® license. The financial support provided by FAPERJ, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, FAPESP, Fundação de Amparo à Pesquisa do Estado de São Paulo, and CNPq, Conselho Nacional de Desenvolvimento Científico e Tecnológico, are also gratefully.


  1. Baier H, Pühlhofer T (2003) Approaches for further rationalization in mechanical architecture and structural design of satellites. In: Proceedings of 54th international astronautical congress, Bremen, Germany.Google Scholar
  2. Coello CAC (2006) Evolutionary multi-objective optimization: a historical view of the field. IEEE Comput Intell Mag 1(1):28–36CrossRefGoogle Scholar
  3. Cuco APC (2011) Development of a multi-objective methodology for layout optimization of equipment in artificial satellites (in Portuguese). Master degree dissertation, Postgraduate Course in Space Technology and Engineering, INPEGoogle Scholar
  4. De Sousa FL, Muraoka I, Galski RL (2007) On the optimal positioning of electronic equipment in space platforms. In: Proceedings of the 19th international congress of mechanical engineering, Brasilia, Brasil 2007Google Scholar
  5. Deb K, Agrawal S, Pratab A, Meyarivan T (2002) A fast elitist nondominated sorting genetic algorithm for multi-objective optimization: NSGA-II. IEEE Trans Evol Comput 6(2):182–197CrossRefGoogle Scholar
  6. Ferebee MJ Jr, Allen CL (1991) Optimization of payload placement on arbitrary spacecraft. J Spacecr Rockets 28(5):612–614CrossRefGoogle Scholar
  7. Ferebee Jr MJ, Powers RB (1987) Optimization of payload mass placement in a dual keel space station. NASA Technical Memorandum 89051, March 1987.Google Scholar
  8. Galski RL, De Sousa FL, Ramos FM (2005) Application of a new multi-objective evolutionary algorithm to the optimum design of a remote sensing satellite constellation. In: Proceedings of the 5th international conference on inverse problems in engineering: theory and practice, vol II. Cambridge, UK G01, 11–15th July 2005.Google Scholar
  9. Hengeveld DW, Braun JE, Eckhard AG, Williams AD (2011) Optimal placement of electronic components to minimize heat flux nonuniformities. J Spacecr Rockets 48(4):556–563CrossRefGoogle Scholar
  10. Hwang JT, Lee DY, Cutler JW, Martins JRRA (2014) Large-scale multidisciplinary optimization of a small satellite’s design and operation. J Spacecr Rockets. doi: 10.2514/1.A32751 Google Scholar
  11. Jackson B, Norgard J (2002) A stochastic optimization for determining spacecraft avionics box placement. In: IEEE Aerospace Conference, vol. 5, pp 2373–2382, 2002Google Scholar
  12. Martins JRRA, Lambe AB (2013) Multidisciplinary design optimization: a survey of architectures. AIAA J 51(9):2049–2075. doi: 10.2514/1.J051895 CrossRefGoogle Scholar
  13. Pühlhofer T, Langer H, Baier H, Huber M (2004) Multicriteria and discrete configuration and design optimization with applications for satellites. In: Proceedings of 10th AIAA/ISSMO multidisciplinary analysis and optimization conference, Albany, 30 Aug, 01 Sept 2004.Google Scholar
  14. Sun Z-G, Teng H-F (2003) Optimal layout design of a satellite module. Eng Optim 35(5):513–529CrossRefGoogle Scholar
  15. Teng H-F, Sun S-L, Liu D-Q, Li Y-Z (2001) Layout optimization for the objects located within a rotating vessel—a three-dimensional packing problem with behavioral constraints. Comput Oper Res 28:521–535CrossRefMATHGoogle Scholar
  16. Teng H-F, Chen Y, Zeng W, Shi Y-J, Hu Q-H (2010) A dual-system variable grain cooperative coevolutionary algorithm: satellite-module layout design. IEEE Trans Evol Comput 14(3):438–455CrossRefGoogle Scholar
  17. Wang Y-S, Teng H-F, Shi Y-J (2009) Cooperative co-evolutionary scatter search for satellite module layout design. Eng Comput 26(7):761–785CrossRefMATHGoogle Scholar
  18. Zhang B, Teng H-F, Shi Y-J (2008) Layout optimization of satellite module using soft computing techniques. Appl Soft Comput 8:507–521CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Ana Paula Curty Cuco
    • 1
  • Fabiano L. de Sousa
    • 2
  • Antônio J. Silva Neto
    • 3
  1. 1.Instituto Nacional de Pesquisas Espaciais – INPE/DMCS.J. CamposBrazil
  2. 2.Instituto Nacional de Pesquisas Espaciais – INPE/DSES.J. CamposBrazil
  3. 3.Universidade do Estado do Rio de Janeiro, IPRJ/UERJNova FriburgoBrazil

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