This paper investigates a decomposition-coordination method using Multi-agent systems implementation for solving the nonlinear equality constrained multiobjective optimization problem (NECMOP), where several nonlinear objective functions must be optimized in a conflicting situation. A practical case study of an unmanned aerial vehicle was found to fit the characteristics of the model and was then taken to test the effectiveness of the method. The NECMOP is converted to an equivalent scalar optimization problem (SOP) which is then decomposed into several separable subproblems. These latter are independent from each other, which makes them processable in parallel and allows nonlinearity to be treated at a local level by an agent which lives in a container. The agents communicate the results to the master agent who coordinates the intermediate solutions using Lagrange multipliers and requests a new loop until it finds an optimal solution that satisfies all the constraints.