Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
A doubly distributed genetic algorithm for network coding
Proceedings of the 9th annual conference on Genetic and evolutionary computation
IEEE Transactions on Information Theory
Information flow decomposition for network coding
IEEE Transactions on Information Theory
Dynamic network coding problem: an evolutionary approach
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
An effective genetic algorithm for network coding
Computers and Operations Research
| Hi-index | 0.00 |
The optimization of network coding is a relatively new area for evolutionary algorithms, as very few efforts have so far been reported. This paper is concerned with the design of an effective Genetic Algorithm (GA) for tackling the network coding problem (NCP). Differing from previous relevant works, the proposed GA is designed based on a permutation representation, which not only allows each chromosome to record a specific network protocol and coding scheme, but also makes it easy to integrate useful problem-specific heuristic rules into the algorithm. In the new GA, a more general fitness function is proposed, which, besides considering the minimization of network coding resources, also takes into account the maximization of the rate actually achieved. This new fitness function makes the proposed GA more suitable for the case of dynamic network coding, where any link could be cut off at any time, and consequently, the target rate might become unachievable even if all nodes allow coding. Based on the new representation and fitness function, other GA related techniques are modified and employed accordingly and carefully. Comparative experiments show that the proposed GA clearly outperforms previous methods.