Furthermore, we present engineering techniques which use structural properties of the line graph to further reduce the ILP size. As a naive ILP formulation is too demanding, we derive a new custom-tailored formulation which requires significantly fewer constraints. LOOM proceeds in three stages: (1) construct a so-called line graph, where edges correspond to segments of the network with the same set of lines following the same course (2) construct an ILP that yields a line ordering for each edge which minimizes the total number of line crossings and line separations (3) based on the line graph and the ILP solution, draw the map. We parse this data from GTFS, the prevailing standard for public transit data. The input to LOOM is data about the lines of a given transit network, namely for each line, the sequence of stations it serves and the geographical course the vehicles of this line take. We present LOOM (Line-Ordering Optimized Maps), a fully automatic generator of geographically accurate transit maps.
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