Within this chapter the multi-objective struggle genetic algorithm is employed to support the design of hydraulic actuation systems. Two concepts, a valve-controlled and a pump-controlled system for hydraulic actuation are evaluated using Pareto optimization. The actuation systems are analyzed using comprehensive dynamic simulation models to which the optimization algorithm is coupled. The outcome from the Pareto optimization is a set of Pareto optimal solutions, which allows visualization of the trade-off between the objectives. Both systems are optimized, resulting in two Pareto fronts that visualize the trade-off between system performance and system cost. By comparing the two Pareto fronts, it could be seen under which perferences a valve system is to be preferred to a pump system. Thus, optimization is employed in order to support concept selection.
Furthermore, general design problems usually constitute a mixture of determining both continuous parameters as well as selecting individual components from catalogs or databases. Therefore the optimization is extended to handle a mixture of continuous parameters and discrete selections from catalogs. The valve-controlled system is again studied, but this time with cylinders and valves arranged in hierarchical catalogs, resulting in a discrete Pareto optimzal front.