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In full generality, minimizing a polynomial function over a closed
semi-algebraic set requires complex mathematical equations. This
book explains recent developments from singularity theory and
semi-algebraic geometry for studying polynomial optimization
problems. Classes of generic problems are defined in a simple and
elegant manner by using only the two basic (and relatively simple)
notions of Newton polyhedron and non-degeneracy conditions
associated with a given polynomial optimization problem. These
conditions are well known in singularity theory, however, they are
rarely considered within the optimization community.Explanations
focus on critical points and tangencies of polynomial optimization,
Hoelderian error bounds for polynomial systems, Frank-Wolfe-type
theorem for polynomial programs and well-posedness in polynomial
optimization. It then goes on to look at optimization for the
different types of polynomials. Through this text graduate
students, PhD students and researchers of mathematics will be
provided with the knowledge necessary to use semi-algebraic
geometry in optimization.
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