An improved collaborative optimization for multidisciplinary problems with coupled design variables

• An improved collaborative optimization was proposed to tackle MDO problems with coupling design variables, especially parametric and parameter-free variables.
• A criterion was proposed to determine the coupling of private variables and public variables within disciplines.
• A strategy was suggested to decouple the coupled variables.
• Two typical examples with or without coupled design variables were comparatively studied to validate the improved collaborative optimization.

In this paper, the collaborative optimization is improved to tackle multidisciplinary problems with coupling design variables within disciplines. The design variables are first distinctly classified into private and public ones according to disciplines. A criterion is then proposed to judge the coupling of private variables with the public variables. For the coupling case, a strategy is suggested to decouple the variables before performing the collaborative optimization. To demonstrate the effectiveness of the improved collaborative optimization, two practical optimization problems are comparatively studied for uncoupled design variables as well as coupled ones. It is shown that the present framework can achieve the better optimal results as compared with other methods. Furthermore, the judge criterion and the decoupling strategy are also validated.