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Abstract

We study the problem of optimizing over the set of all combinatorial embeddings of a given planar graph. Our objective function prefers certain cycles of $G$ as face cycles in the embed ding. The motivation for studying this problem arises in graph drawing, where the chos en embedding has an important influence on the aesthetics of the drawing. We characterize the set of all possible embeddings of a given biconnected planar graph $G$ by means of a system of linear inequalities with $\{0,1\}$-variables corresponding to the set of those cycles in $G$ which can appear in a combinator ial embedding. This system of linear inequalities can be constructed recursively using SPQR-trees and a new splitting operation. Our computational results on two benchmark sets of graphs are surprising: The nu mber of variables and constraints seems to grow only linearly with the size of the graphs although the number of embeddings grows exponentially. For all tested graphs (up to 500 vertices) and l inear objective functions, the resulting integer linear programs could be generated within 10 mi nutes and solved within two seconds on a Sun Enterprise 10000 using CPLEX.