Abstract: To improve the efficiency of calculation of robust collaborative optimization(RCO) model and the optimization performance of solution method, a new robust collaborative optimization model based on IUP(SIUPRCO) and an improved solution method(IRCORM) are presented. The solution of global sensitivity equation is avoided and the efficiency of calculation is improved in SIUPRCO model. In the initial stage of IRCORM algorithm, to avoid the phenomenon that the optimization results of RCO usually converge to the local extremum, the dynamic penalty function method is adopted to get the global extremum without considering the uncertainty factor and the optimization result is used as the initial point of RCO. The Pareto-optimal solutions are obtained by using traversal combination method. Two typical examples are adopted to test the two presented methods. The results show that the SIUPRCO model is reasonable and the IRCORM method has good optimization performance.

Key words: Dynamic penalty function, Pareto-optimal solutions, Robust collaborative optimization, Uncertainty