GraphDrawer
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                            <div xmlns="http://www.w3.org/1999/xhtml" class="FulltextWrapper"><div class="ArticleHeader main-context"><div id="enumeration" class="enumeration"><p class="test-LocationInConferenceProceeding"><span data-test="ConferenceAcronym">GD 2001</span>: <span class="BookTitle"><a href="https://link.springer.com/book/10.1007/3-540-45848-4" class="gtm-book-link">Graph Drawing</a></span><span class="page-numbers-info">
                pp 31-44</span><span class="u-inline-block u-ml-4"> |
                <a class="gtm-cite-link" href="#citeas">Cite as</a></span></p></div><div class="MainTitleSection"><h1 class="ChapterTitle" lang="en">Fast and Simple Horizontal Coordinate Assignment</h1></div><div class="authors u-clearfix authors--enhanced" data-component="SpringerLink.Authors"><ul class="u-interface u-inline-list authors__title" data-role="AuthorsNavigation"><li><a href="#authors" class="gtm-tab-authors selected">Authors</a></li><li><a href="#authorsandaffiliations" class="gtm-tab-authorsandaffiliations">Authors and affiliations</a></li></ul><span class="marker" style="width: 160px;"></span><div class="authors__list" data-role="AuthorsList" id="authors"><ul class="test-contributor-names"><li itemscope="" itemtype="http://schema.org/Person" class="u-mb-2 u-pt-4 u-pb-4"><span itemprop="name" class="authors__name">Ulrik&nbsp;Brandes</span></li><li itemscope="" itemtype="http://schema.org/Person" class="u-mb-2 u-pt-4 u-pb-4"><span itemprop="name" class="authors__name">Boris&nbsp;Köpf</span></li></ul></div><div class="authors__affiliations" id="authorsandaffiliations"><div class="authors-affiliations u-interface"><ul class="test-contributor-names"><li itemscope="" itemtype="http://schema.org/Person" class="u-mb-2 u-pt-4 u-pb-4"><span itemprop="name" class="authors-affiliations__name">Ulrik&nbsp;Brandes</span><ul class="authors-affiliations__indexes u-inline-list" data-role="AuthorsIndexes"><li data-affiliation="affiliation-1">1</li></ul></li><li itemscope="" itemtype="http://schema.org/Person" class="u-mb-2 u-pt-4 u-pb-4"><span itemprop="name" class="authors-affiliations__name">Boris&nbsp;Köpf</span><ul class="authors-affiliations__indexes u-inline-list" data-role="AuthorsIndexes"><li data-affiliation="affiliation-1">1</li></ul></li></ul><ol class="test-affiliations"><li class="affiliation" data-test="affiliation-1" data-affiliation-highlight="affiliation-1" itemscope="" itemtype="http://schema.org/Organization"><span class="affiliation__count">1.</span><span class="affiliation__item"><span itemprop="department" class="affiliation__department">Department of Computer &amp; Information Science</span><span itemprop="name" class="affiliation__name">University of Konstanz</span><span itemprop="address" itemscope="" itemtype="http://schema.org/PostalAddress"><span itemprop="addressRegion" class="affiliation__city">Konstanz</span><span itemprop="addressCountry" class="affiliation__country">Germany</span></span></span></li></ol></div></div></div><div class="main-context__container" data-component="SpringerLink.ArticleMetrics"><div class="main-context__column"><span><span class="test-render-category">Conference paper</span></span><div class="article-dates" data-component="SpringerLink.ArticleDates"><div class="article-dates__entry"><span class="article-dates__label">First Online: </span><span class="article-dates__first-online"><time datetime="2002-02-21">21 February 2002</time></span></div><div class="article-dates__history"></div></div></div><div class="main-context__column">    <ul id="book-metrics" class="article-metrics u-sansSerif">
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                            <span id="chaptercitations-count-number" class="test-metric-count c-button-circle gtm-chaptercitations-count">9</span>
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                Part of the
                <a class="gtm-book-series-link" href="https://link.springer.com/bookseries/558">Lecture Notes in Computer Science</a>
                book series (LNCS, volume 2265)</span></div><section class="Abstract" id="Abs1" tabindex="-1" lang="en"><h2 class="Heading">Abstract</h2><p class="Para">We
 present a simple, linear-time algorithm to determine horizontal 
coordinates in layered layouts subject to a given ordering within each 
layer. The algorithm is easy to implement and compares well with 
existing approaches in terms of assignment quality.</p></section><div class="KeywordGroup" lang="en"><h2 class="Heading">Keywords</h2><span class="Keyword">Layered Graph&nbsp;</span><span class="Keyword">Minimum Separation&nbsp;</span><span class="Keyword">Vertical Alignment&nbsp;</span><span class="Keyword">Bend Point&nbsp;</span><span class="Keyword">Graph Drawing&nbsp;</span><div id="test-keyword-message" class="u-interface u-italic">
							These keywords were added by machine and not by the authors. This
 process is experimental and the keywords may be updated as the learning
 algorithm improves.
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    </div></div><section class="Section1 RenderAsSection1" id="Bib1" tabindex="-1"><h2 class="Heading" data-role="collapsible-handle">References<span class="section-icon"></span></h2><div class="content"><ol class="BibliographyWrapper"><li class="Citation"><div class="CitationNumber">1.</div><div class="CitationContent" id="CR1">Oliver Bastert and Christian Matuszewski. Layered drawings of digraphs. In Michael Kaufmann and Dorothea Wagner, editors, <em class="EmphasisTypeItalic ">Drawing Graphs: Methods and Models</em>, volume 2025 of <em class="EmphasisTypeItalic ">Lecture Notes in Computer Science</em>, pages 104–139. 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