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Tunneling Algorithm for Solving Nonconvex Optimal Control Problems

In: Optimization, Simulation, and Control

Author

Listed:
  • Alexander Yurievich Gornov

    (Institute for System Dynamics and Control Theory SB RAS)

  • Tatiana Sergeevna Zarodnyuk

    (Institute for System Dynamics and Control Theory SB RAS)

Abstract

This chapter considers a new method of search for the global extremum in a nonlinear nonconvex optimal control problem. The method employs a curvilinear search technique to implement the tunneling phase of the algorithm. Local search in the minimization phase is carried out with the standard algorithm that combines the methods of conjugate and reduced gradients. The software implementation of the suggested tunneling algorithm was tested on a collection of nonconvex optimal control problems and demonstrated efficiency of the this approach.

Suggested Citation

  • Alexander Yurievich Gornov & Tatiana Sergeevna Zarodnyuk, 2013. "Tunneling Algorithm for Solving Nonconvex Optimal Control Problems," Springer Optimization and Its Applications, in: Altannar Chinchuluun & Panos M. Pardalos & Rentsen Enkhbat & E. N. Pistikopoulos (ed.), Optimization, Simulation, and Control, edition 127, pages 289-299, Springer.
    • Handle: RePEc:spr:spochp:978-1-4614-5131-0_18
    DOI: 10.1007/978-1-4614-5131-0_18
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    Cited by:

    1. Alexander Yu. Gornov & Tatiana S. Zarodnyuk & Anton S. Anikin & Evgeniya A. Finkelstein, 2020. "Extension technology and extrema selections in a stochastic multistart algorithm for optimal control problems," Journal of Global Optimization, Springer, vol. 76(3), pages 533-543, March.

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