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Bacterial Foraging‐Tabu Search Metaheuristics for Identification of Nonlinear Friction Model

Author

Listed:
  • Nuapett Sarasiri
  • Kittiwong Suthamno
  • Sarawut Sujitjorn

Abstract

This paper proposes new metaheuristic algorithms for an identification problem of nonlinear friction model. The proposed cooperative algorithms are formed from the bacterial foraging optimization (BFO) algorithm and the tabu search (TS). The paper reports the search comparison studies of the BFO, the TS, the genetic algorithm (GA), and the proposed metaheuristics. Search performances are assessed by using surface optimization problems. The proposed algorithms show superiority among them. A real‐world identification problem of the Stribeck friction model parameters is presented. Experimental setup and results are elaborated.

Suggested Citation

  • Nuapett Sarasiri & Kittiwong Suthamno & Sarawut Sujitjorn, 2012. "Bacterial Foraging‐Tabu Search Metaheuristics for Identification of Nonlinear Friction Model," Journal of Applied Mathematics, John Wiley & Sons, vol. 2012(1).
    • Handle: RePEc:wly:jnljam:v:2012:y:2012:i:1:n:238563
    DOI: 10.1155/2012/238563
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    References listed on IDEAS

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    1. Fred Glover, 1990. "Tabu Search—Part II," INFORMS Journal on Computing, INFORMS, vol. 2(1), pages 4-32, February.
    2. Roberto Battiti & Giampietro Tecchiolli, 1994. "The Reactive Tabu Search," INFORMS Journal on Computing, INFORMS, vol. 6(2), pages 126-140, May.
    3. Nowicki, Eugeniusz & Smutnicki, Czeslaw, 1996. "A fast tabu search algorithm for the permutation flow-shop problem," European Journal of Operational Research, Elsevier, vol. 91(1), pages 160-175, May.
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    Cited by:

    1. Gintaras Palubeckis, 2013. "An Improved Exact Algorithm for Least‐Squares Unidimensional Scaling," Journal of Applied Mathematics, John Wiley & Sons, vol. 2013(1).

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