![]() ![]() ![]() On Convergence Rates of Subgradient Optimization Methods. European Journal of Operational Research, 58:149–172. ![]() Topological Design of Computer Communication Networks - the Overall Design Problem. Topological Design of Telecommunication Networks - Survey of Local Access Network Design Methods. Formulations and Algorithms for the Capacitated Minimal Directed Tree Problem. Topological Design of Centralized Computer Networks - Formulations and Algorithms. A Dual-Based Procedure for Uncapacited Facilities Location. Exact and Approximate Algorithm for Optimal Network Design. European Journal of Operational Research, 50:280–297.ĭionne, R. A Comparison of Heuristics and Relaxations for the Capacited Plant Location Problem. John Wiley and Sons, New York, NY.Ĭornuéjols, G., R. Francis (eds), Discrete Location Theory, pages 119–172. The Uncapacited Facility Location Problem. Location of Banks Account to Optimise Float: An Analytic Study of Exact and Approximate Algorithm. Oxford University Press, Oxford.Ĭornuéjols, G., M. The Combinatorics of Network Reliability. European Journal of Operational Research, 12(1):19–28.Ĭolbourn, C.J. Extension to a Lagrangian Relaxation Approach for the Capacitated Warehouse Location Problem. To appear in Annals of Operations Research.Ĭhristofides, N. Effective Formulation for the Two Level Simple Plant Location Problem. Springer Verlag, Berlin.Ĭhardaire, P., J.-L. Valqui Vidal (ed), Applied Simulated Annealing, Lecture Notes Series, pages 175–199. Using Simulated Annealing to Solve Concentrator Location Problems in Telecommunication Networks. Computer Networks and ISDN Systems, 11:139–146.Ĭhardaire, P. Grade of Service and Optimization of Distributed Packet-Switched Networks. Solving the Dynamic Facility Location Problem. European Journal of Operational Research, 65:383–399.Ĭhardaire, P., M.C. Lagrangean Heuristics for Location Problems. European Journal of Operational Research, 33:314–325.īeasley, J.E. An Algorithm for Solving Large Capacitated Wharehouse Location Problems. European Journal of Operational Research, 53:38–45.īeasley, J.E. Computational Results from a New Lagrangian Relaxation Algorithm for the Capacited Plant Location Problem. Modeling and Worst-Case Performance Analysis of the Two-Level Network Design Problem. A Dual-Based Algorithm for Multi-Level Network Design Problem. Mathematics of Operations Research, 13:1–31.īalakrishnan, A., T.L. Probabilistic Analysis of a Relaxation for the k-Median Problem. Correction of printing errors in 211253-256Īhn, S., C. Mathematics of Operations Research 203562–582. Capacitated Facility Location Valid Inequalities and Facets. This process is experimental and the keywords may be updated as the learning algorithm improves.Īardal K. These keywords were added by machine and not by the authors. ■ the evaluation of the network in terms of performance and reliability. ![]() ■ the assignment of terminals to backbone nodes, ■ the choice of locations for backbone nodes, A standard approach involves the following phases (Minoux, 1989 Gavish, 1991): The design of a telecommunication network is so complex that the process is usually split into phases where each phase handles a subproblem and makes decisions that are fixed and used as input to the next phases (Gavish, 19). Communication channels between terminals are established through their access nodes via the backbone network. The backbone network enables the transfer of large volumes of information between its nodes whereas each local access network connects a group of terminals to an access node of the backbone network. Social Networks, 39, 84 – 97.A telecommunication network is usually composed of a backbone network and of local access networks. The backbone of bipartite networks: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors. backbone: An R package for backbone extraction of weighted graphs. Analysis of spatial networks from bipartite projections using the R backbone package. Comparing alternatives to the fixed degree sequence model for extracting the backbone of bipartite projections. backbone: An R package to extract network backbones. ![]()
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