Soft Computing

, Volume 19, Issue 9, pp 2619–2632 | Cite as

Heuristic and genetic algorithms for solving survivability problem in the design of last mile communication networks

Methodologies and Application

Abstract

Given a connected, undirected and weighted graph \(G = (V, E)\), a set of infrastructure nodes \(J\) and a set of customers \(C\) include two customer types whereby customers \(C_{1}\) require a single connection (type-1) and customers \(C_{2}\) need to be redundantly connected (type-2). Survivable network design problem (SNDP) seeks a sub-graph of \(G\) with the smallest weight in which all customers are connected to infrastructure nodes. SNDP has applications in the design of the last mile of the real-world communication networks. SNDP is NP-hard so heuristic approaches are normally adopted to solve this problem, especially for large-scale networks. This paper proposes a new heuristic algorithm and a new genetic algorithm for solving SNDP. The proposed algorithms are experimented on real-world instances and random instances. Results of computational experiments show that the proposed heuristic algorithm is much more efficient than the other heuristics in running time, and the proposed genetic algorithm is much more efficient than the other heuristics in terms of minimizing the network cost.

Keywords

Survivable network design  Fiber optic network Shortest paths Edge-disjoint paths  Heuristic algorithm  Genetic algorithm 

Notes

Acknowledgments

This work was supported by the project “Models for the next generation of a robust Internet,” Grant Number 12/2012/HD-NDT, funded by the Ministry of Science and Technology, Vietnam.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.School of Information and Communication TechnologyHanoi University of Science and TechnologyHanoiVietnam

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