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We present an application of efficient evolutionary algorithm on the time optimal trajectory planning of a manipulator. The proposed method is simple, flexible and provides a near optimal solution among the huge trajectory space. We first outline the differences in the trajectory parameterization method between the evolutionary algorithm and the conventional nonlinear programming based approach. Then, we propose two novel evolutionary schemes and investigate their characteristics. The first scheme is based upon the canonical genetic algorithm (GA) and the penalty function method to tackle the torque constraints. The second scheme, which is basically based on evolutionary strategy (ES), incorporates effective heuristics to further speed up the search and utilizes the time scaling method to deal with the constraints on actuator torques. The effectiveness and validity of the proposed method are demonstrated through the simulation study in comparison with other conventional nonlinear programming based methods.