In clinical trials, problems arise frequently when multiple tests are performed. Multiplicity may have a substantial influence on the rate of false positive conclusions. Therefore, control of Type I error rate  is an important concern when designing clinical trials. Several statistical approaches have been developed to allow this control in case of multiple objectives. This work focuses on the use of gatekeeping strategies for multiplicity adjustments in case of multiple objectives in clinical trials. The principle of gatekeeping strategies is to test in a sequential manner objectives which are hierarchically ordered. Depending on the study design, different types of gatekeeping strategy can be used to control the Type I error: serial, parallel and tree-structured gatekeeping strategies. Here, an illustration of two strategies is exposed. We evaluate the performance of three different scenarios, two serial scenarios and a parallel one, with multiple objectives through several simulations of clinical trial data. We also study the performance variations in case of correlated data. We find that increasing the correlation may have an effect on the performance of scenarios.