Network Migration Optimization Using Genetic Algorithms
Abstract
This paper introduces the problem of communication network migration for backbone networks. Heuristic solutions for this problem can be determined by the application of genetic algorithms to the problem. A description of the system model is presented, as well as the used algorithmic approaches and optimization results. Our main goal is the optimization of migration costs, by respecting increasing demands over the migration period, while device costs per bit are decreasing. We will present Crowded DPGA as best found GA to solve the network migration problem.
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