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The authors develop an adaptive and efficient Genetic Algorithm (GA) to solve the dynamic Routing, Modulation and Spectrum Assignments (RMSA) for elastic O-OFDM networks. The algorithm offers an efficient way of serving the dynamic light-path requests based on the current network status at each service provision time. The GA is designed for multi-objective optimization. For low traffic cases when there is no blocking, the GA minimizes the maximum number of slots required on any fiber in the network; otherwise, it minimizes the blocking probability. The performance of the proposed GA is evaluated in dynamic RMSA simulations with the 14-node NSFNET and the 28-node US Backbone topologies, and the results show that it converges within 25 generations.
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