Opumal trajectory plannmg for robot naanlpulators plays an important role in maplementmg the high productivity for robots. The performance indexes used in optimal trajectory planning are classified into two mam categories: optimum traveling tmie and optmmm mechanical energy of the actuators. The current trajectory planning algorithms are designed based on one of the above two perfomaance indexes. So far, there have been few planning algorithms designed to satisfy two performance indexes simultaneously. On the other hand, some deficiencies arise m the existing integrated optimJzataon algonthms of trajectory planning. In order to overcome those deficiencies, the integrated opumization algorithms of trajectory planning are presented based on the complete analysis for trajectory phnrurtg of robot manipulators. In the algorithm, two object functions are designed based on the specific weight coefficient method and "ideal point" strategy. Moreover, based on the features of optimizataon problem, the intensified evolutionary progranmamg ts proposed to solve the corresponding optmalzataon model. Especially, for the Stanford Robot, the high-quality solutaons are found at a lower cost.