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

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 $$\mathrm{{G}} = (\mathrm{V, E})$$G=(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.

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