An aircraft basically is a closed energy system, carrying energy consumers as well as the fuel from which this energy is generated. The elements in the conversion chains in between determine the performance (mass, efficiency) of the system. This study involves the development of a flexible framework that manages and optimizes the performance of such chains. It links any number of component simulations in standardized modules together, with the energy flow between two components being the connecting parameter. To optimize the power flow in networks with a high diversity in component simulation fidelity and for multiple objectives, a genetic algorithm is used (the elitist Non-dominated Sorting Genetic Algorithm NSGA-2). Because of the complexity of jet engines, an external gas turbine simulation package has been integrated as an essential building block. A simple demonstration network was optimized for minimum mass and energy required to satisfy demand in each flight phase and the framework was found to perform as expected.