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

Bui, L.T. and Thi Thanh Binh, H. (2016) A survivable design of last mile communication networks using multi-objective genetic algorithms. Memetic Computing, 8 (2). pp. 97-108. ISSN 18659284

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Abstract

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 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. © 2016, Springer-Verlag Berlin Heidelberg.

Item Type: Article
Divisions: Faculties > Faculty of Information Technology
Identification Number: 10.1007/s12293-015-0177-7
Uncontrolled Keywords: Computational complexity; Costs; Genetic algorithms; Sales; Computational experiment; Multi objective; Multi-objective genetic algorithm; Network costs; Set of customers; Single connection; Survivable network design; Undirected graph; Graph theory
Additional Information: Language of original document: English.
URI: http://eprints.lqdtu.edu.vn/id/eprint/9831

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