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Planarizing Graphs  A Survey and Annotated Bibliography
, 1999
"... Given a finite, undirected, simple graph G, we are concerned with operations on G that transform it into a planar graph. We give a survey of results about such operations and related graph parameters. While there are many algorithmic results about planarization through edge deletion, the results abo ..."
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Cited by 33 (0 self)
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Given a finite, undirected, simple graph G, we are concerned with operations on G that transform it into a planar graph. We give a survey of results about such operations and related graph parameters. While there are many algorithmic results about planarization through edge deletion, the results about vertex splitting, thickness, and crossing number are mostly of a structural nature. We also include a brief section on vertex deletion. We do not consider parallel algorithms, nor do we deal with online algorithms.
A Better Approximation Algorithm for Finding Planar Subgraphs
 J. ALGORITHMS
, 1996
"... The MAXIMUM PLANAR SUBGRAPH problemgiven a graph G, find a largest planar subgraph of Ghas applications in circuit layout, facility layout, and graph drawing. No previous polynomialtime approximation algorithm for this NPComplete problem was known to achieve a performance ratio larger than ..."
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Cited by 29 (4 self)
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The MAXIMUM PLANAR SUBGRAPH problemgiven a graph G, find a largest planar subgraph of Ghas applications in circuit layout, facility layout, and graph drawing. No previous polynomialtime approximation algorithm for this NPComplete problem was known to achieve a performance ratio larger than 1=3, which is achieved simply by producing a spanning tree of G. We present the first approximation algorithm for MAXIMUM PLANAR SUBGRAPH with higher performance ratio (4=9 instead of 1=3). We also apply our algorithm to find large outerplanar subgraphs. Last, we show that both MAXIMUM PLANAR SUBGRAPH and its complement, the problem of removing as few edges as possible to leave a planar subgraph, are Max SNPHard.
Planarization of Graphs Embedded on Surfaces
 in WG
, 1995
"... A planarizing set of a graph is a set of edges or vertices whose removal leaves a planar graph. It is shown that, if G is an nvertex graph of maximum degree d and orientable genus g, then there exists a planarizing set of O( p dgn) edges. This result is tight within a constant factor. Similar res ..."
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Cited by 7 (1 self)
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A planarizing set of a graph is a set of edges or vertices whose removal leaves a planar graph. It is shown that, if G is an nvertex graph of maximum degree d and orientable genus g, then there exists a planarizing set of O( p dgn) edges. This result is tight within a constant factor. Similar results are obtained for planarizing vertex sets and for graphs embedded on nonorientable surfaces. Planarizing edge and vertex sets can be found in O(n + g) time, if an embedding of G on a surface of genus g is given. We also construct an approximation algorithm that finds an O( p gn log g) planarizing vertex set of G in O(n log g) time if no genusg embedding is given as an input. 1 Introduction A graph G is planar if G can be drawn in the plane so that no two edges intersect. Planar graphs arise naturally in many applications of graph theory, e.g. in VLSI and circuit design, in network design and analysis, in computer graphics, and is one of the most intensively studied class of graphs [2...
A linear algorithm for finding a maximal planar subgraph
 SIAM J. Disc. Math
, 2006
"... Abstract. We construct an optimal lineartime algorithm for the maximal planar subgraph problem: given a graph G, find a planar subgraph G ′ of G such that adding to G ′ an extra edge of G results in a nonplanar graph. Our solution is based on a fast data structure for incremental planarity testing ..."
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Cited by 4 (0 self)
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Abstract. We construct an optimal lineartime algorithm for the maximal planar subgraph problem: given a graph G, find a planar subgraph G ′ of G such that adding to G ′ an extra edge of G results in a nonplanar graph. Our solution is based on a fast data structure for incremental planarity testing of triconnected graphs and a dynamic graph search procedure. Our algorithm can be transformed into a new optimal planarity testing algorithm. Key words. Planar graphs, planarity testing, incremental algorithms, graph planarization, data structures, triconnectivity. AMS subject classifications. 05C10, 05C85, 68R10, 68Q25, 68W40 1. Introduction. Agraphisplanar
Apptopinv  user’s guide
, 2003
"... The maximum planar subgraph, maximum outerplanar subgraph, the thickness and outerthickness of a graph are all NPcomplete optimization problems. Apptopinv is a program that contains different heuristic algorithms for these four problems: algorithms based on HopcroftTarjan planarity testing algorit ..."
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Cited by 1 (1 self)
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The maximum planar subgraph, maximum outerplanar subgraph, the thickness and outerthickness of a graph are all NPcomplete optimization problems. Apptopinv is a program that contains different heuristic algorithms for these four problems: algorithms based on HopcroftTarjan planarity testing algorithm, the spanningtree heuristic and various algorithms based on the cactustree heuristic. Apptopinv contains also a simulated annealing algorithm that can be used to improve the solutions obtained from other heuristics. Most of the heuristics have also a greedy version. We have implemented graph generators for complete graphs, complete kpartite graphs, complete hypercubes, random graphs, random maximum planar and outerplanar graphs and random regular graphs. Apptopinv supports three different graph file formats. Apptopinv is written in C++ programming language for Linuxplatform and GCC 2.95.3 compiler. To compile the program, a commercial LEDA algorithm