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A solving tool for fuzzy quadratic optimal control problems

Author

Listed:
  • Silvio Giove

    () (Department of Applied Mathematics, University of Venice)

  • Paolo Bortot

    () (Department of Applied Mathematics, University of Venice)

Abstract

In this paper we propose an iterative method to solve an optimal control problem, with fuzzy target and constraints. The algorithm is developed in such a way as to satisfy the target function and the constraints. The algorithm can be applied only if a method exists to solve a crisp parametric sub-problem obtained by the original one. This is the case for a quadratic-linear target function with linear constraints, for which some well established solvable methods exist for the crisp associated sub-problem. A numerical test confirmed the good convergence properties.

Suggested Citation

  • Silvio Giove & Paolo Bortot, 2006. "A solving tool for fuzzy quadratic optimal control problems," Working Papers 148, Department of Applied Mathematics, Universit√† Ca' Foscari Venezia.
  • Handle: RePEc:vnm:wpaper:148
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    References listed on IDEAS

    as
    1. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    2. Inuiguchi, Masahiro & Sakawa, Masatoshi, 1995. "Minimax regret solution to linear programming problems with an interval objective function," European Journal of Operational Research, Elsevier, vol. 86(3), pages 526-536, November.
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    More about this item

    Keywords

    fuzzy; mathematical programming;

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

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