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Stochastic Method for the Solution of Unconstrained Vector Optimization Problems

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Abstract

We propose a new stochastic algorithm for the solution of unconstrained vector optimization problems, which is based on a special class of stochastic differential equations. An efficient algorithm for the numerical solution of the stochastic differential equation is developed. Interesting properties of the algorithm enable the treatment of problems with a large number of variables. Numerical results are given.

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Authors and Affiliations

  1. Universität der Bundeswehr, EIT 1, Neubiberg, Germany

    S. Schäffler (Professor of Mathematics)

  2. Corporate Technology, Siemens AG, München, Germany

    R. Schultz (Scientist)

  3. Automation and Control, Siemens AG, Erlangen, Germany

    K. Weinzierl (Engineer)

Authors
  1. S. Schäffler
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  2. R. Schultz
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  3. K. Weinzierl
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Schäffler, S., Schultz, R. & Weinzierl, K. Stochastic Method for the Solution of Unconstrained Vector Optimization Problems. Journal of Optimization Theory and Applications 114, 209–222 (2002). https://doi.org/10.1023/A:1015472306888

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  • DOI: https://doi.org/10.1023/A:1015472306888

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