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Annals of Computer Science and Information Systems, Volume 5

Proceedings of the 2015 Federated Conference on Computer Science and Information Systems

Genetic Algorithms for Balanced Spanning Tree Problem

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DOI: http://dx.doi.org/10.15439/2015F249

Citation: Proceedings of the 2015 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 5, pages 537545 ()

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Abstract. Given an undirected weighted graph G=(V,E) with vertex set V and edge set E and a designated vertex r in V, we consider the problem of constructing a spanning tree in G that balances both the minimum spanning tree and the shortest paths tree rooted at r. Formally, for any two constants A,B > =1, we consider the problem of computing an (A,B)-balanced spanning tree T in G, in the sense that, (i) for every vertex v in V, the distance between r and v in T is at most A times the shortest distance between the two vertices in G, and (ii) the total weight of T is at most B times that of the minimum tree weight in G. It is well known that, for any A, B > = 1, the problem of deciding whether G contains an (A,B)-balanced spanning tree is NP-complete. Consequently, given any A > = 1 (resp., B > = 1), the problem of finding an (A,B)-balanced spanning tree that minimizes B (resp., A) is NP-complete. In this paper, we present efficient genetic algorithms for these problems. Our experimental results show that the proposed algorithm returns high quality balanced spanning trees.