A multiobjective thermal power dispatch problem is formulated using noncommensurable objectives such as operating costs and minimal emission. A sensitivity measure is chosen whereby the effects of variations in the nominal conditions describing a given multiobjective problem can be measured and incorporated as a performance index to be minimized. A nonlinear programming problem provides the framework for examining the objective constraint level in an ε-constant form of the multiobjective optimization problem. The dispersion index is chosen as the sensitivity measure for the investigation of the effects of random variations in the model parameters of the optimal solution. A sensitivity trade-off is exploited for the multiobjective problem that represents the trade-off between sensitivity and objective level. Validity of the method has been demonstrated by analysing a three-generator sample system.