Loading and unloading operations are widely employed in industrial robots and CNC machine tools. In the present study, an effective algorithm is established for optimum time-jerk path planning and reducing the vibration of the serial manipulator, and enhancing the robot efficiency. To this end, the manipulator’s trajectory is constructed using quintic B-spline interpolation in the joint space and the optimal objective function is constructed in terms of time and mean jerk. A hybrid improved whale optimization and particle swarm optimization (IWOA-PSO) method is proposed to optimize the objective function. First, WOA is improved by employing adaptive weight and threshold to balance exploration and exploitation of the WOA to prevent falling into the local optimum solution. Then, PSO method and IWOA techniques are combined to enhance the convergence speed of the IWOA. Applying different algorithms to 23 benchmark functions demonstrate superiority of the proposed algorithm to state-of-the-art algorithms. A 6-DOF serial industrial manipulator integrated in CNC machine was taken as a case study and the joint positions are considered the IWOA-PSO inputs. All calculations are performed in the MATLAB 2018b environment. The obtained results demonstrate that the proposed IWOA-PSO can effectively reduce the jerk of the robot while improving its work efficiency.