Exploring Local Optima in Schematic Layout

Abstract—In search-based graph drawing methods there are typically a number of parameters that control the search algo-rithm. These parameters do not affect the fitness function, but nevertheless have an impact on the final layout. One such search method is hill climbing, and, in the context of schematic layout, we explore how varying three parameters (grid spacing, the starting distance of allowed node movement and the number of iterations) affects the resultant diagram. Although we cannot characterize schematics completely and so cannot yet automatically assign parameters for diagrams, we observe that when parameters are set to values that increase the search space, they also tend to improve the final layout. We come to the conclusion that hill-climbing methods for schematic layout are more prone to reaching local optima than had previously been expected and that a wider search, as described in this paper, can mitigate this, so resulting in a better layout. I