Novel parallel particle swarm optimization algorithms applied on the multi-task cooperation

With more and more applications of workflow technology, the workflow systems must be flexible and dynamic in order to effectively adapt for the uncertain and error-prone collaborative work environments. This paper adds the interaction and machine learning to the workflow model proposed by workflow management coalition and then applies the parallel particle swarm optimization algorithm to solve it, so that workflow modeling and enactment are both flexible while the complexity of whole system is decrease. The improvement based on the model manifest that it not only realizes the flexible workflow, but also supports the personality of workflow.