Skip to main content
Log in

An external penalty-type method for multicriteria

  • Original Paper
  • Published:
TOP Aims and scope Submit manuscript

Abstract

We propose an extension of the classical real-valued external penalty method to the multicriteria optimization setting. As its single objective counterpart, it also requires an external penalty function for the constraint set, as well as an exogenous divergent sequence of nonnegative real numbers, the so-called penalty parameters, but, differently from the scalar procedure, the vector-valued method uses an auxiliary function, which can be chosen among large classes of “monotonic” real-valued mappings. We analyze the properties of the auxiliary functions in those classes and exhibit some examples. The convergence results are similar to those of the scalar-valued method, and depending on the kind of auxiliary function used in the implementation, under standard assumptions, the generated infeasible sequences converge to weak Pareto or Pareto optimal points. We also propose an implementable local version of the external penalization method and study its convergence results.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  • Bonnel H, Iusem AN, Svaiter BF (2005) Proximal methods in vector optimization. SIAM J Optim 15(4):953–970

    Article  Google Scholar 

  • Carrizosa E, Frenk JBG (1998) Dominating sets for convex functions with some applications. J Optim Theory Appl 96(2):281–295

    Article  Google Scholar 

  • Eschenauer H, Koski J, Osyczka A (1990) Multicriteria design optimization. Springer, Berlin

    Book  Google Scholar 

  • Fliege J, Graña Drummond LM, Svaiter BF (2009) Newton’s method for multiobjective optimization. SIAM J Optim 20(2):602–626

    Article  Google Scholar 

  • Fliege J, Svaiter BF (2000) Steepest descent methods for multicriteria optimization. Math Methods Oper Res 51(3):479–494

    Article  Google Scholar 

  • Fu Y, Diwekar U (2004) An efficient sampling approach to multiobjective optimization. Ann Oper Res 132(1–4):109–134

    Article  Google Scholar 

  • Fukuda EH, Graña Drummond LM (2011) On the convergence of the projected gradient method for vector optimization. Optimization 60(8–9):1009–1021

    Article  Google Scholar 

  • Fukuda EH, Graña Drummond LM (2013) Inexact projected gradient method for vector optimization. Comput Optim Appl 54(3):473–493

    Article  Google Scholar 

  • Graña Drummond LM, Iusem AN (2004) A projected gradient method for vector optimization problems. Comput Optim Appl 28(1):5–29

    Article  Google Scholar 

  • Graña Drummond LM, Raupp FMP, Svaiter BF (2014) A quadratically convergent Newton method for vector optimization. Optimization 63(5):661–677

    Article  Google Scholar 

  • Graña Drummond LM, Svaiter BF (2005) A steepest descent method for vector optimization. J Comput Appl Math 175(2):395–414

    Article  Google Scholar 

  • Gravel M, Martel JR, Price W, Tremblay R (1992) A multicriterion view of optimal ressource allocation in job-shop production. Eur J Oper Res 61:230–244

    Article  Google Scholar 

  • Jahn J (2003) Vector optimization—theory, applications, and extensions. Springer, Erlangen

  • Leschine TM, Wallenius H, Verdini W (1992) Interactive multiobjective analysis and assimilative capacity-based ocean disposal decisions. Eur J Oper Res 56:278–289

    Article  Google Scholar 

  • Luc DT (1989) Theory of vector optimization. In: Lecture notes in economics and mathematical systems, 319. Springer, Berlin

  • Luenberger DG (2003) Linear and nonlinear programming. Kluwer Academic Publishers, Boston

    Google Scholar 

  • Tavana M (2004) A subjective assessment of alternative mission architectures for the human exploration of mars at NASA using multicriteria decision making. Comput Oper Res 31:1147–1164

    Article  Google Scholar 

  • White DJ (1984) Multiobjective programming and penalty functions. J Optim Theory Appl 43(4):583–599

    Article  Google Scholar 

  • White DJ (1998) Epsilon-dominating solutions in mean-variance portfolio analysis. Eur J Oper Res 105:457–466

    Article  Google Scholar 

  • Zangwill WI (1967) Non-linear programming via penalty functions. Manag Sci 13(5):344–358

    Article  Google Scholar 

Download references

Acknowledgments

We would like to thank the anonymous referees for their suggestions which improved the original version of the paper. We are also thankful to Alfredo N. Iusem and Benar F. Svaiter for valuable discussions.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ellen H. Fukuda.

Additional information

This work was supported by Grant-in-Aid for Young Scientists (B) (26730012) from Japan Society for the Promotion of Science and a Grant (311165/2013-3) from National Counsel of Technological and Scientific Development (CNPq).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fukuda, E.H., Drummond, L.M.G. & Raupp, F.M.P. An external penalty-type method for multicriteria. TOP 24, 493–513 (2016). https://doi.org/10.1007/s11750-015-0406-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11750-015-0406-8

Keywords

Mathematics Subject Classification

Navigation