Routing in a network with unreliable components

A new approach to the joint selection of primary and secondary routes in a network with unreliable components is presented. The mathematical model captures the changes in the operational characteristics of the network as it adapts to failures. Lagrangian relaxation and subgradient optimization techniques are used to obtain good heuristic solutions to the problem, as well as lower bounds to be used as benchmarks against which the quality of the solution is assessed. Results of numerical experiments are reported, and directions for further enhancements of the model are discussed. >