— For complex optimization problems, several population-based heuristics like Multi-Objective Evolutionary Algorithms have been developed. These algorithms are aiming to deliver ...
One of the new trends in genetic fuzzy systems (GFS) is the use of evolutionary multiobjective optimization (EMO) algorithms. This is because EMO algorithms can easily handle two c...
During the optimization of a constrained problem using evolutionary algorithms (EAs), an individual in the population can be described using three important properties, i.e., obje...
—In metabolic engineering it is difficult to identify which set of genetic manipulations will result in a microbial strain that achieves a desired production goal, due to the co...
It is not unusual that an approximate model is needed for fitness evaluation in evolutionary computation. In this case, the convergence properties of the evolutionary algorithm are...