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Multi-objective Model Predictive Control

In: Multiple Criteria Decision Making for Sustainable Energy and Transportation Systems

Author

Listed:
  • Hirotaka Nakayama

    (Konan University)

  • Yeboon Yun
  • Masakazu Shirakawa

Abstract

Model predictive (or sequential approximate) optimization methods find an optimal solution in parallel with predicting the function forms in mathematical models when those forms are not known explicitly in terms of design variables. In this paper, under a dynamic environment with multiple objectives, we propose a model predictive optimization method using computational intelligence in particular support vector regression and the satisficing trade-off method. The effectiveness of the proposed method will be shown along a numerical example.

Suggested Citation

  • Hirotaka Nakayama & Yeboon Yun & Masakazu Shirakawa, 2010. "Multi-objective Model Predictive Control," Lecture Notes in Economics and Mathematical Systems, in: Matthias Ehrgott & Boris Naujoks & Theodor J. Stewart & Jyrki Wallenius (ed.), Multiple Criteria Decision Making for Sustainable Energy and Transportation Systems, pages 277-287, Springer.
    • Handle: RePEc:spr:lnechp:978-3-642-04045-0_24
    DOI: 10.1007/978-3-642-04045-0_24
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    Cited by:

    1. Jeffrey P Perley & Judith Mikolajczak & Marietta L Harrison & Gregery T Buzzard & Ann E Rundell, 2014. "Multiple Model-Informed Open-Loop Control of Uncertain Intracellular Signaling Dynamics," PLOS Computational Biology, Public Library of Science, vol. 10(4), pages 1-15, April.

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