This article briefly discusses methods for finding Pareto-optimal solutions for multi-criteria problems in the conditions of uncertainty. It is noted that the quality of management depends on the adequacy of the rule base for the selected fuzzy controller set by experts. The conditions for the final decision of the choice of the Pareto-optimal fuzzy solution are determined. An algorithm for the method of estimating the Pareto-optimal solution taking into account utility is developed and presented. Multicriteria optimization of the functioning of control systems is considered when setting local criteria in the form of fuzzy intervals. Scalarization methods that are used in ranking criteria are considered. Quantitative determination of the criterion is applicable if its numerical comparison is possible. The objective function is determined by local criteria. Optimization is associated with the search for control actions that provide optimal values of the multidimensional objective function. For problems with threshold optimization, a similar estimate can also be obtained. Given that, when analyzing solution options, complexity scales are constructed, an estimate of the time to build the complexity scale is also introduced. The application of the threshold optimization method to search for the Pareto optimal solution is considered. An approach to evaluating Pareto-optimal solutions using the criteria for evaluating utility is proposed. An algorithm has been developed to evaluate the Pareto-optimal solution taking into account utility.