<div class="csl-bib-body">
<div class="csl-entry">Nöllenburg, M., & Terziadis, S. (2023). Computing Data-driven Multilinear Metro Maps. <i>Cartographic Journal</i>, <i>60</i>(4), 367–382. https://doi.org/10.1080/00087041.2024.2304476</div>
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dc.identifier.issn
0008-7041
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/205808
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dc.description.abstract
Traditionally, most schematic metro maps in practice as well as metro map layout algorithms adhere to an octolinear layout style with all paths composed of horizontal, vertical, and 45◦-diagonal edges. Despite growing interest in more general multilinear metro maps, generic algorithms to draw metro maps based on a system of k ≥ 2 not necessarily equidistant slopes have not been investigated thoroughly. In this paper, we present and implement an adaptation of the octolinear mixed-integer linear programming approach of Nöllenburg and Wolff (2011) that can draw metro maps schematized to any set C of arbitrary orientations. We further present a data-driven approach to determine a suitable set C by either detecting the best rotation of an equidistant orientation system or by clustering the input edge orientations using a k-medians algorithm. We demonstrate the new possibilities of our method using several real-world examples.