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Mathematically Rigorous Global Optimization and Fuzzy Optimization

In: Black Box Optimization, Machine Learning, and No-Free Lunch Theorems

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  • Ralph Baker Kearfott

    (University of Louisiana at Lafayette)

Abstract

Mathematically rigorous global optimization and fuzzy optimization have different philosophical underpinnings, goals, and applications. However, some of the tools used in implementations are similar or identical. We review, compare and contrast basic ideas and applications behind these areas, referring to some of the work in the very large literature base.

Suggested Citation

  • Ralph Baker Kearfott, 2021. "Mathematically Rigorous Global Optimization and Fuzzy Optimization," Springer Optimization and Its Applications, in: Panos M. Pardalos & Varvara Rasskazova & Michael N. Vrahatis (ed.), Black Box Optimization, Machine Learning, and No-Free Lunch Theorems, pages 169-194, Springer.
    • Handle: RePEc:spr:spochp:978-3-030-66515-9_7
    DOI: 10.1007/978-3-030-66515-9_7
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