Abstract
Network coding can reduce the data transmission time and improves the throughput and transmission efficiency. However, network coding technique increases the complexity and overhead of network because of extra coding operation for information from different links. Therefore, network coding optimization problem becomes more and more important. In this paper, a differential evolution algorithm based on simulated annealing (SDE) is proposed to solve the network coding optimization problem. SDE introduces individual acceptance mechanism based on simulated annealing into canonical differential evolution algorithm. SDE finds out the optimal solution and keeps the population diversity during the process of evolution and avoids falling into local optimum as far as possible. Simulation experiments show that SDE can improve the local optimum of DE and finds network coding scheme with less coding edges.
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Zhang, L., Zhuo, X., Zhao, X. (2015). Research on Network Coding Optimization Using Differential Evolution Based on Simulated Annealing. In: Tan, Y., Shi, Y., Buarque, F., Gelbukh, A., Das, S., Engelbrecht, A. (eds) Advances in Swarm and Computational Intelligence. ICSI 2015. Lecture Notes in Computer Science(), vol 9140. Springer, Cham. https://doi.org/10.1007/978-3-319-20466-6_37
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DOI: https://doi.org/10.1007/978-3-319-20466-6_37
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