A Hybrid Evolutionary Algorithm for the Page Number Minimization Problem

Satsangi, Dharna; Srivastava, Kamal; Gursaran,

doi:10.1007/978-3-642-24043-0_47

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Cited by 2 publications

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“…The literature contains similar greedy optimization algorithms for the VO [21,35], another simulated annealing approach [33], evolutionary [24,32], and neural network algorithms [28,37]. However, they all were either restricted to only two pages or were outperformed by other heuristics in previous experiments [26].…”

Section: Local Search Heuristicsmentioning

confidence: 99%

Experimental Evaluation of Book Drawing Algorithms

Klawitter

Mchedlidze

Nöllenburg

2018

Lecture Notes in Computer Science

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A k-page book drawing of a graph G = (V, E) consists of a linear ordering of its vertices along a spine and an assignment of each edge to one of the k pages, which are half-planes bounded by the spine. In a book drawing, two edges cross if and only if they are assigned to the same page and their vertices alternate along the spine. Crossing minimization in a k-page book drawing is NP-hard, yet book drawings have multiple applications in visualization and beyond. Therefore several heuristic book drawing algorithms exist, but there is no broader comparative study on their relative performance. In this paper, we propose a comprehensive benchmark set of challenging graph classes for book drawing algorithms and provide an extensive experimental study of the performance of existing book drawing algorithms.

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