The hop-limit approach for spare-capacity assignment in survivable networks
IEEE/ACM Transactions on Networking (TON)
Virtual path routing for survivable ATM networks
IEEE/ACM Transactions on Networking (TON)
Path selection and bandwidth allocation in MPLS networks
Performance Evaluation - Special issue: Internet performance and control of network systems
Implementing Traffic Engineering in MPLS-Based IP Networks with Lagrangean Relaxation
ISCC '03 Proceedings of the Eighth IEEE International Symposium on Computers and Communications
Computational Optimization and Applications
Routing, Flow, and Capacity Design in Communication and Computer Networks
Routing, Flow, and Capacity Design in Communication and Computer Networks
ISCC '04 Proceedings of the Ninth International Symposium on Computers and Communications 2004 Volume 2 (ISCC"04) - Volume 02
Mesh-based Survivable Transport Networks: Options and Strategies for Optical, MPLS, SONET and ATM Networking
ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartI
A new approach to survivability of connection oriented networks
ICCS'03 Proceedings of the 1st international conference on Computational science: PartI
Evolutionary algorithm for congestion problem in connection-oriented networks
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part IV
Prioritized traffic restoration in connection oriented QoS based networks
Computer Communications
IEEE Communications Magazine
Anycasting in connection-oriented computer networks: Models, algorithms and results
International Journal of Applied Mathematics and Computer Science - Computational Intelligence in Modern Control Systems
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Our discussion in this article centers on the application of a Lagrangean relaxation and a subgradient optimization technique to the problem of primary route assignment (PRA) in survivable connection-oriented networks. The PRA problem consists in a static optimization of primary routes minimizing the Lost Flow in Node (LFN) function. The major contribution of this work is a combination of the Lagrangean relaxation with other heuristic algorithms. We evaluate the performance of the proposed Lagrangean-based heuristic by making a comparison with their counterparts including evolutionary algorithm and GRASP using various network topologies and demand patterns. The results of simulation tests show that the new algorithm provides sub-optimal results, which are better than other heuristics.