Design evolution and synthesis of multi-domain engineering systems using artificial immune system

A multidisciplinary design method is developed in this paper to optimally evolve and synthesize multi-domain engineering systems. The design methodology utilizes two navigated optimization loops to handle the optimization of both topology and parameters. In the topology optimization, which is the outer loop, the proposed artificial immune system (AIS) tool, which contains a clonal selection algorithm (CLONALG) and negative selection techniques, is utilized to synthesize the number and the structure of the elements. A novel concept of “artificial vaccination” is developed, which is responsible for the incorporation of domain knowledge. In the inner loop, an optimization tool that incorporates simple AIS is utilized for parameter tuning in any generated topology. By acquiring knowledge and learning from prior trials, the evolution parameters are automatically and intelligently tuned to make the design model more reliable and to facilitate more effective navigation. Numerical study on the design of a hydraulic engine mount is presented. The results indicate that the proposed design flowchart enables the designers to successfully modify (specifically, extend or reduce) the initial colony in order to obtain the optimal solution.