Exploring Local Optima in Schematic Layout

In search-based graph drawing methods there are

typically a number of parameters that control the search algorithm.

These parameters do not affect the ?tness function, but

nevertheless have an impact on the ?nal 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 ?nal layout. We come to the conclusion that hillclimbing

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.