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Tracing the Pareto frontier in bi-objective optimization problems by ODE techniques

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Abstract

In this paper we present a deterministic method for tracing the Pareto frontier in non-linear bi-objective optimization problems with equality and inequality constraints. We reformulate the bi-objective optimization problem as a parametric single-objective optimization problem with an additional Normalized Normal Equality Constraint (NNEC) similar to the existing Normal Boundary Intersection (NBI) and the Normalized Normal Constraint method (NNC). By computing the so called Defining Initial Value Problem (DIVP) for segments of the Pareto front and solving a continuation problem with a standard integrator for ordinary differential equations (ODE) we can trace the Pareto front. We call the resulting approach ODE NNEC method and demonstrate numerically that it can yield the entire Pareto frontier to high accuracy. Moreover, due to event detection capabilities available for common ODE integrators, changes in the active constraints can be automatically detected. The features of the current algorithm are illustrated for two case studies whose Matlab® code is available as Electronic Supplementary Material to this article.

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References

  1. Allgower, E.L., Georg, K.: Introduction to Numerical Continuation Methods. Society for Industrial and Applied Mathematics, Philadelphia, PA, USA (2003)

    Book  MATH  Google Scholar 

  2. Coleman, T.F., Zhang, Y.: Optimization Toolbox User’s Guide, Version 5. 3 Apple Hill Drive, Natick, MA 01760-2098 (2010)

  3. Das, I., Dennis, J.E.: A closer look at drawbacks of minimizing weighted sums of objectives for Pareto set generation in multicriteria optimization problems. Struct. Optim. 14, 63–69 (1997)

    Article  Google Scholar 

  4. Das, I., Dennis, J.E.: Normal-Boundary Intersection: a new method for generating the Pareto surface in nonlinear multicriteria optimization problems. SIAM J. Optim. 8, 631–657 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  5. Haimes, Y.Y., Lasdon, L.S., Wismer, D.A.: On a bicriterion formulation of the problems of integrated system identification and system optimization. IEEE Trans. Syst. Man Cybern. SMC-1, 296–297 (1971)

    MathSciNet  Google Scholar 

  6. Hillermeier, C.: Generalized homotopy approach to multiobjective optimization. J. Optim. Theory Appl. 110, 557–583 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  7. Messac, A., Ismail-Yahaya, A., Mattson, C.A.: The normalized normal constraint method for generating the Pareto frontier. Struct. Multidiscipl. Optim. 25, 86–98 (2003)

    Article  MathSciNet  Google Scholar 

  8. Miettinen, K.: Nonlinear Multiobjective Optimization. Kluwer Academic Publishers, Boston (1999)

    MATH  Google Scholar 

  9. Rakowska, J., Haftka, R.T., Watson, L.T.: Tracing the efficient curve for multi-objective control-structure optimization. Comput. Syst. Eng. 2, 461–471 (1991)

    Article  Google Scholar 

  10. Shampine, L.F., Reichelt, M.W.: The Matlab ODE suite. SIAM J. Sci. Comput. 18, 1–22 (1997)

    Article  MathSciNet  MATH  Google Scholar 

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Correspondence to Andreas Potschka.

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Potschka, A., Logist, F., Van Impe, J.F. et al. Tracing the Pareto frontier in bi-objective optimization problems by ODE techniques. Numer Algor 57, 217–233 (2011). https://doi.org/10.1007/s11075-010-9425-6

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  • DOI: https://doi.org/10.1007/s11075-010-9425-6

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