Grid Workflow Scheduling based on improved genetic algorithm

Grid Workflow Scheduling represented by DAG(Directed Acyclic Graph) is a typical NP-complete problem, and thus a scheduling algorithm of high efficiency is required. So an improved genetic algorithm is proposed to solve this problem. In the algorithm, chromosomes of poor fitness make secondary preferential hybridization and mutation with the overall best individual. It not only guarantees the population diversity but increases the convergence rate of population. Experiment results based on Gridsim prove it available and better than standard genetic algorithm.