Research of Routing Optimization Algorithms Based on Ahn Improved Genetic Algorithms
Shao Lin-lin · Computers & Security · 2009
This paper presents an Ahn Improved genetic algorithmic to solve shortest path routing optimization problem. Variable-length chromosomes and their genes are used for encoding the problem. The crossover operation exchanges partial chromosomes (partial-routes) at positional independent crossing sites and the mutation operation maintains the genetic diversity of the population. The algorithm can cure all the infeasible chromosomes with a simple repair operation. Crossover and mutation together provide a search capability that results in improved quality of solution and enhanced rate of convergence. Computer simulations have verified that the algorithm is efficient and effective.