Algorithm 797: Fortran subroutines for approximate solution of graph planarization problems using GRASP

Authors:
Celso C. Ribeiro;Mauricio G. C. Resende
Affiliations:
Catholic Univ. of Rio de Janeiro, Rio de Janeiro, Brazil;AT&T Labs Research, Florham Park, NJ
Venue:
ACM Transactions on Mathematical Software (TOMS)
Year:
1999

Citing 3
Cited 2

An O(m log n)-time algorithm for the maximal planar subgraph problem

SIAM Journal on Computing
Efficient Planarity Testing

Journal of the ACM (JACM)
Algorithmic Graph Theory and Perfect Graphs (Annals of Discrete Mathematics, Vol 57)

Algorithmic Graph Theory and Perfect Graphs (Annals of Discrete Mathematics, Vol 57)

Probability Distribution of Solution Time in GRASP: An Experimental Investigation

Journal of Heuristics
Exploiting run time distributions to compare sequential and parallel stochastic local search algorithms

Journal of Global Optimization

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Abstract

We describe Fortran subroutines for finding approximate solutions of the maximum planar subgraph problem (graph planarization) using a Greedy Randomized Adaptive Search Procedure (GRASP). The design and implementation of the code are described in detail. Computational results with the subroutines illustrate the quality of solutions found as a function of number of GRASP iterations.