I am using a genetic algorithm for the optimization of a thermodynamic cycle. The problem has no analytical solution and the solution space is computationally large. The question is the following: How can i combine 2 or more objective functions with different value range and dimensions into a single multi-objective function that has to be maximized or minimized? The usual methods involve some kind of normalization using minimum and maximum values of the single-objective functions. The problem is that it would take a significant amount of time to explore the solution space. Is there an alternative?