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Jean B Lasserre(lasserrelaas.fr) Abstract: We consider the inverse optimization problem associated with the polynomial program $f^*=\min \{f(x):x\inK\}$ and a given current feasible solution $y\in K$. We provide a numerical scheme to compute an inverse optimal solution. That is, we compute a polynomial $\tilde{f}$ (which may be of same degree as $f$ if desired) with the following properties: (a) $y$ is a global minimizer of $\tilde{f}$ on $K$ with a Putinar's certificate with an a priori degree bound fixed, and (b), $\tilde{f}$ minimizes $\Vert f\tilde{f}\Vert$ (which can be the $\ell_1$, $\ell_2$ or $\ell_\infty$norm of the coefficients) over all polynomials with such properties. Computing $\tilde{f}_d$ reduces to solving a semidefinite program whose optimal value also provides a bound on how far is $f(y)$ from the unknown optimal value $f^*$. The size of the semidefinite program can be adapted to the computational capabilities available. Moreover, if one uses the $\ell_1$norm, then $\tilde{f}$ takes a simple and explicit {\it canonical} form. Some variations are also discussed. Keywords: nverse optimization; positivity certificate; mathematical programming; global optimization; semidefinite programming Category 1: Global Optimization (Theory ) Category 2: Linear, Cone and Semidefinite Programming (Semidefinite Programming ) Category 3: Other Topics (Other ) Citation: Download: [PDF] Entry Submitted: 03/21/2011 Modify/Update this entry  
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