Real World System Architecture Design Using Multi-criteria Optimization: A Case Study

System architecture design using multi-criteria optimization is demonstrated using a case study of an aero engine health management (EHM) system. A design process for optimal deployment of EHM system functional operations over physical architecture component locations, e.g., on-engine, on-aircraft and on-ground, is described. The EHM system architecture design needs to be optimized with respect to many qualitative criteria in terms of operational attributes within the constraints of resource limitations. In this paper the system architecture design problem is formulated as a multi-criteria optimization problem. Considering the large discrete search space of decision variables and many-objective functions and constraints, an evolutionary multi-objective genetic algorithm along with a progressive preference articulation technique, is used for solving the optimization problem. The optimization algorithm found a family of Pareto solutions which provided valuable insight into design trade-offs. Using the progressive preference articulation technique, the optimization search can be focused for the industrial decision maker on to a region of interest in the objective space. Performance of the proposed method is evaluated using various test metrics. Using this approach it was possible to identify the most significant design constraints (“hot spots”) and the opportunities afforded by either the relaxation or the tightening of these constraints, along with their performance implications.