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Abstract
The analysis of sensitivity of efficient solutions to changes in the preference structure of the designer is presented as a way to improve the efficiency of interactive multiobjective optimization problems. Sensitivity analysis is used to predict new efficient solutions and to generate information that can guide the designer in the search for more satisfactory designs in the efficient set. This information is generated without additional function or gradient evaluations, making the method particularly suited to problems involving a lengthy analysis. The procedure can be implemented effectively when the optimization is performed by sequential quadratic programming algorithms. Examples of this implementation are provided for illustration.