Abstract: Research on workflow business hours一cost optimization problem. hhis paper proposed a novel dynamic par- tick swarm algorithm optimization method of workflow service subject. hhrough regional division, in each of the parti- cles located in the region, when adapting to a value less than the best fitness, reinitializes region, so that the algorithm has better global convergence and dynamic adaptability, while the introduction of random disturbance, reverse operator, the search scope arc expanded to the entire solution space in order to greatly improve the optimal solution probability. Combined with dynamic particle swarm algorithm based grid workflow scheduling problem of target model, and from three aspects of the cross time granularity, across time zones, the across working system, this paper discussed the work- flow service subject selection method. The experimental results show that this method than other applications of grid workflow scheduling algorithm has shorter execution time and cost,higher efficiency,better superiority.

Key words: Dynamic particle swarm, Workflow, Scheduling, Uenetic algorithm