This paper deals with optimizing the task cycle time of industrial robots integrated in complex robot cells. Trajectory optimizers are usually based on models and can't properly deal with uncertainties due to interactions between the robot and its environment. We propose here a trajectory optimizer with hardware in the loop which can take into account constraints such as maximum authorized temperature and maximum authorized torque. Our approach is based on unconstrained optimization algorithms without derivatives and penalty methods. Experiments on real industrial applications showed good robustness properties of this algorithm even with a high number of parameters and with changes of the robot task.