Multiple Objective Optimization with Vector Evaluated Genetic Algorithms


Genetic algorithms (GA'S) have been shown to be capable of searching for optima in function spaces which cause difficulties for gradient techniques. This paper presents a method by which the power of GA's can be applied to the optimization of multiobjective functions.