Research on multi-objective multidisciplinary design optimization based on particle swarm optimization

Complex systems consist of many disciplines or components, which are often difficult to the design optimize as a overall. They need to be broken down into different components, and then coordinate the links between different parts. ATC (Analysis Target Cascade) - one of the multidisciplinary design optimization methods, is an effective way to solve such intricate problems. In the traditional multidisciplinary design optimization methods, there is only one objective function. But the multi-objective optimization problems are often emerged in practical engineering problems. So, we will focus on the multi-objective optimization problems in multidisciplinary design optimization, and solve them with particle swarm optimization. The original problem is firstly decomposed into multiple coupled sub-problems and then coordinate the relation between each sub-problems by ATC method. The system-level sub-problem is a multi-objective optimization problem and the other subsystems are the general single-objective optimization problems, the MOPSO method and the sequence quadratic programming (SQP) method will be used to solve them respectively. The final optimization result is consistent with the optimization result before the original problem is decomposed. Finally, we used two examples to demonstrate the feasibility of particle swarm optimization (PSO) method to get the solution of the multi-objective problems with ATC method.