Memetic Computing

, Volume 8, Issue 2, pp 97–108 | Cite as

A survivable design of last mile communication networks using multi-objective genetic algorithms

  • Lam Thu Bui
  • Huynh Thi Thanh Binh
Regular Research Paper


In this paper, we are interested in the survivable network design problem (SNDP) for last mile communication networks called (L-SNDP). Given a connected, weighted, undirected graph \(\mathrm{{G}} = (\mathrm{V, E})\); a set of infrastructure nodes and a set of customers C including two customer types where customers in the subset C1 require a single connection (type-1) and customers in the subset C2 need to be redundantly connected (type-2). The aim is to seek a sub-graph of G with the smallest weight in which all customers are connected to infrastructure nodes and the connections are protected against failures. This is a NP-hard problem and it has been solved only with the objective of minimizing the network cost. In this paper, we introduce a new multi-objective approach to solve L-SNDP called ML-SNDP. These objectives are to minimize the network cost (total cost) and to minimize the maximal amount of sharing links between connections. Results of computational experiments reported show the efficiency of our proposal.


Survivable network design Multi-objective genetic algorithm 



This work was supported by the project “Advanced methods in Evolutionary Computation in approximating solutions for combinatorial optimization problems”, Grant no. 102.01-2015.12, funded by National Foundation for Science and Technology Development, Vietnam.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Le Quy Don Technical UniversityHanoiVietnam
  2. 2.Hanoi University of Science and TechnologyHanoiVietnam

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