Many real world engineering problems are characterized by the presence of several conflicting design objectives. In this paper, a new multi-objective genetic algorithm is employed to optimize two different concepts of hydraulic actuation systems. The different concepts have been modeled in a simulation environment to which the optimization strategy has been coupled.
The outcome from the proposed optimization strategy is a set of Pareto optimal solutions elucidating the tradeoffs between competing objectives. By comparing Pareto frontiers for competing concepts, valuable insights about the properties of the different concepts can be gained. Depending on how the decision-maker values the different objectives, different design solutions are more appropriate. This is exemplified in the hydraulic actuation systems, where the acceptance of a larger control error results in a design with low energy consumption.