There is an increasing demand to optimize performance and profit of comminution circuits. Research in this area has resulted in the development of numerous optimization tools, and recent research has shown that the quality aspects of the production have a great influence on the optimization results. The quality, cost, profit and capacity of a product are influenced by several parameters, and in order to control all of these parameters it is necessary to use some sort of optimization algorithm. In this paper, a novel approach to apply e.g. cost, revenue, capacity and quality in order to perform a multi objective optimization with the ability to handle dynamic variations of a comminution is presented. The problem with optimizations in general is that the objective function used for optimization is reduced in complexity in order to save computational time. In a comminution process performance varies with time and in order to perform a correct optimization the objective function used must be able to handle this type of dynamic behavior. The process has a given set of constraints that represents the conditions normal in these type of comminution applications. The first step in this paper is to identify if the range of the constraints can cause undesirable production costs when reaching for a given produet property. In this step a dynamic response model is described that will be able to address the difficulties with optimizing dynamic systems. The next step in the optimization is the definition of the multi-objective optimization formulation including constraints for the optimization. Evaluating the result of the optimization in combination with a strategy for relaxing constraint can show how to increase overall productivity and still reach certain product properties. The conclusions made in this work are that multi objective optimization is essential when optimizing a comminution circuit against multiple objectives. (C) 2016 Elsevier Ltd. All rights reserved.