\contentsline {table}{\numberline {3.1\relax }{\ignorespaces $\unhbox \voidb@x \hbox {Faces, complementary faces, residual subspaces in } {\cal R}^{n}_+,\nobreakspace {}{\cal S}^{n}_{+},\nobreakspace {}K_p $}}{36}
\contentsline {table}{\numberline {5.1\relax }{\ignorespaces Choices for the scaling matrix $P$.}}{122}
\contentsline {table}{\numberline {5.2\relax }{\ignorespaces Indicators of the status of problem $(D)$ via the embedding of $(D)$ and $(P)$, if $(P)$ and ($D$) satisfy Assumption 5.8.1\hbox {}.}}{136}
\contentsline {table}{\numberline {5.3\relax }{\ignorespaces Duality relations for a given problem $(D)$, its gapfree dual $(P_{gf})$ and its corrected problem $(D_{cor})$. }}{137}
\contentsline {table}{\numberline {6.1\relax }{\ignorespaces Linear mappings $\Phi _{\bf \Delta }$ associated with various sets ${\bf \Delta } \subseteq {\unhbox \voidb@x \hbox {\bf R}}^{N \times N}$. The notation $Z_{kj}$, $k,j \in \{1,2\}$, refers to corresponding $N \times N$ blocks in matrix $Z \in {\cal S}^{2N}$, and $Z_{jj}(i)$ denotes the $i$-the diagonal block of $Z_{jj}$, of size $r_i \times r_i$.}}{148}
\contentsline {table}{\numberline {8.1\relax }{\ignorespaces Correspondence between linear and semidefinite programming}}{233}
\contentsline {table}{\numberline {11.1\relax }{\ignorespaces Max-Cut, $n_{K}=20$, $n_{A}=8$, $\delta =10^{-5}$.}}{332}
\contentsline {table}{\numberline {11.2\relax }{\ignorespaces Max-Cut, $n_{K}=20$, $n_{A}=8$, $\delta =10^{-5}$.}}{333}
\contentsline {table}{\numberline {11.3\relax }{\ignorespaces Max-Cut, $n_{K}=8$, $n_{A}=10$, $\delta =10^{-5}$, time limit one hour.}}{333}
\contentsline {table}{\numberline {11.4\relax }{\ignorespaces Arguments for generating the graphs $G_{55}$ to $G_{67}$ by the graph generator {\tt rudy} as communicated by S.\nobreakspace {}Benson.}}{334}
\contentsline {table}{\numberline {11.5\relax }{\ignorespaces $\vartheta $-function, $n_{K}=8$, $n_{A}=10$, $\delta =10^{-5}$, time limit one hour.}}{334}
\contentsline {table}{\numberline {11.6\relax }{\ignorespaces PLDI, $n \geq 500$}}{336}
\contentsline {table}{\numberline {12.1\relax }{\ignorespaces SDP approximation for EQP by iteratively adding sign constraints. The number and largest violation of sign constraints are displayed together with computation time and the lower bound.}}{356}
\contentsline {table}{\numberline {12.2\relax }{\ignorespaces LP-based approximation for EQP. Improvement using triangle inequalities.}}{356}
\contentsline {table}{\numberline {16.1\relax }{\ignorespaces Network performance measures.}}{476}
\contentsline {table}{\numberline {16.2\relax }{\ignorespaces Comparison of LP and SDP relaxations for the network of Figure 16.1\relax \relax \hbox {}.}}{482}
\contentsline {table}{\numberline {16.3\relax }{\ignorespaces Comparison of LP and SDP relaxations for a multiclass queue.}}{484}
\contentsline {table}{\numberline {17.1\relax }{\ignorespaces Sensitivity function for various optimality criteria.}}{518}
\contentsline {table}{\numberline {18.1\relax }{\ignorespaces data for closest distance matrix: dimension; tolerance for duality gap; density of nonzeros in $H$; rank of optimal $X$; number of iterations; cpu-time for one least squares solution of the GN and restricted GN directions. }}{541}
\contentsline {table}{\numberline {18.2\relax }{\ignorespaces data for dual-step-first (20 problems per test); dimension; tolerance for duality gap; density of nonzeros in $H$/ density of infinite values in $H$; positive semidefiniteness of $A$; positive definiteness of $H$; min and max number of iterations; average number of iterations. }}{544}
\contentsline {table}{\numberline {18.3\relax }{\ignorespaces data for primal-step-first (20 problems per test): dimension; tolerance for duality gap; density of nonzeros in $H$/ density of infinite values in $H$; positive semidefiniteness of $A$; positive definiteness of $H$; min and max number of iterations; average number of iterations. }}{545}