Abstract: Reasonable resource scheduling can greatly improve the utilization of the grid. Genetic algorithm (GA) for powerful and implicit parallel space search capability is widely used to solve task allocation and scheduling problems. Based on the research on existing scheduling algorithms, this paper describes the adaptive selection probability combined with niche technology, PCC(parents and children competition) crossover operator, insert mutation operator and elitist strategy to improve GA , it keeps the population's convergence and increases the efficiency of local and global search capability. Simulation results show that this algorithm is more effective for the allocation of resources compared with other algorithm, it can be successfully applied to independent task allocation and scheduling in grid.

Key words: grid, genetic algorithm, task allocation and scheduling