Genetic Representations for Evolutionary Minimization of Network Coding Resources

Abstract. We demonstrate how a genetic algorithm solves the problem of minimizing the resources used for network coding, subject to a throughput constraint, in a multicast scenario. A genetic algorithm avoids the computational complexity that makes the problem NP-hard and, for our experiments, greatly improves on sub-optimal solutions of established methods. We compare two different genotype encodings, which tradeoff search space size with fitness landscape, as well as the associated genetic operators. Our finding favors a smaller encoding despite its fewer intermediate solutions and demonstrates the impact of the modularity enforced by genetic operators on the performance of the algorithm.

• Type: Conference
• Year: 2007
• Where: EVOW
• Authors: Minkyu Kim, Varun Aggarwal, Una-May O'Reilly, Muriel Médard, Wonsik Kim
• Keywords: Artificial Intelligence, Associated Genetic Operators, EVOW 2007, Genetic Algorithm, Genetic Operators