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In dual response surface optimization, the mean and the standard deviation responses are often in conflict. To obtain a satisfactory compromise, a Decision Maker (DM)’s preference information on the tradeoffs between the responses should be incorporated into the problem. In most of the existing works, the DM expresses the subjective judgment on the responses through a preference parameter before the problem solving process, and then a single solution is obtained. In this work, we propose posterior preference articulation approach to dual response surface optimization. The posterior preference articulation approach first finds a set of nondominated solutions without the DM’s preference information, and then enables the DM to select the best one among the nondominated solutions.