Pareto Frontier Construction. A GA vs Gauss-Newton Optimization for Normalized Normal Constraint Method

Important efforts have been made in the last years to develop methods for the construction of Pareto frontiers that guarantee uniform distribution and that exclude the non Pareto and local Pareto points. Nevertheless, these methods are susceptible of improvement or modifications to reach the same level of results more efficiently. This paper presents GA optimization as alternative for normalized normal constraint method. Moreover a compare between Gauss-Newton and GA methods is presented. The results presented in this paper show the suitable behavior of the GA method compared to classical Gauss-Newton methods