The CleanEra project is initialed by the Faculty of Aerospace Engineering at Delft University of Technology. Significant reduction of noise impact on communities around airports is considered as one of the major targets of the project. In this paper, an optimization study is carried out in order to find global optimal trajectories for arriving passenger aircraft, in which the number of awakenings is selected as the objective function. Interval-related optimization algorithms are developed to solve such a highly nonlinear dynamic optimization problem. What differs from conventional optimization algorithms is that intervals rather than real numbers are evaluated in the entire course of optimization. Interval analysis is introduced as the core of such optimization algorithms and a flowchart is presented to show how the algorithms operate when solving practical optimization problems. A noise model, a population distribution model and a sleep disturbance model are connected to demonstrate the feasibility of the developed optimization tool for the considered airspace and aircraft. The result of an example shows that the tool is able to reduce the number of awakenings compared with that from a three-degree decelerating approach.