Abstract: Some serious computational difficulties are found in application of collaborative optimization (CO). Reasons that cause computational difficulties in CO were analyzed. The L₁ norm was used to improve subsystem consistency constraint and to avoid discontinuities in subsystem object function derivatives. Mathematical theory proved the convergency of the improve subsystem consistency constraint. Penalty function was added to system-level object function to convert unconstrained optimization into constrained optimization. A quick-start strategy was used to make the best use of optimal solution of system-level optimization in subsystem-level optimization. A new improved collaborative optimization (ICO) method was presented. Improved subsystem consistency constraint, system-level penalty function, and the quick-start strategy were used in ICO. These measures overcome the computational difficulties of CO better. Experiment results show that the robustness, reliability and computing efficiency of ICO are higher than those of CO.