Network Optimization based on Genetic Algorithm and Estimation of Distribution Algorithm

Genetic algorithm (GA) is a kind of algorithm that simulates the process and the mechanism of the evolution. Because of its unique biologic feature and its suitability to any function, it becomes very popular and has been used in many problems in many fields. Estimation of distribution algorithm (EDA) is an algorithm that is generated from the GAs. Comparing with GAs, the EDAs replace the crossover and the mutation operations in GAs with learning and sampling the probability distribution of the best individuals of the population at each iteration of the algorithm. Because of its superior, it becomes a hot topic recently. Based on the former researches, this paper mainly focuses on solving the problem of one primary network model named all-terminal network model using the strategies of the evolutionary algorithms.