Computing strong metric dimension of some special classes of graphs by genetic algorithms

Computing strong metric dimension of some special classes of graphs by genetic algorithms

In this paper we consider the NP-hard problem of determining the strong metric dimension of graphs. The problem is solved by a genetic algorithm that uses binary encoding and standard genetic operators adapted to the problem. This represents the first attempt to solve this problem heuristically. We...

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Bibliographic Details
Published in:Yugoslav Journal of Operations Research Vol. 18; no. 2; pp. 143 - 151
Main Authors: Kratica Jozef, Kovačević-Vujčić Vera, Čangalović Mirjana
Format: Journal Article
Language:English
Published: University of Belgrade 01-01-2008
Subjects:
evolutionary approach
genetic algorithms
strong metric dimension
Online Access:Get full text
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Summary:In this paper we consider the NP-hard problem of determining the strong metric dimension of graphs. The problem is solved by a genetic algorithm that uses binary encoding and standard genetic operators adapted to the problem. This represents the first attempt to solve this problem heuristically. We report experimental results for the two special classes of ORLIB test instances: crew scheduling and graph coloring.
ISSN:0354-0243
1820-743X
DOI:10.2298/YJOR0802143K