AbstractIn this paper, it is assumed that the ambiguous requirement and desired level of the decisionmaker for the objective functions in the multiobjective nonlinear programming problem can be quantified by eliciting the corresponding membership functions interactively. Then the region for the desired solution, called fuzzy satisficing region, is specified for the membership function by a membership value (required membership value) which is the minimum‐required value to be achieved, and another membership value (desired membership value), which should desirably be achieved. For such a fuzzy satisficing region of the decisionmaker, the penalty and the barrier functions are used to maximize the overachievement for the required membership value, and to minimize the underachievement for the desired membership value. In this way, the Pareto‐optimal solution for the specified fuzzy satisficing region is presented to the decisionmaker. The decisionmaker is either satisfied with the achieved Pareto‐optimal solution, or updates, on subjective basis, the required and the desired membership values. By reducing the fuzzy satisficing region in this way, it is possible eventually to derive the solution satisfactory to the decisionmaker from the set of Pareto‐optimal solutions for the given problem, through relatively simple interactive processes. An interactive computer program is constructed based on the proposed method, and an example for the course of interaction is shown for a numerical