Improving the Non-dominate Sorting Genetic Algorithm for Multi-objective Optimization
Vahid Seydi, M. Ahmadieh Khanehsar, Mohammad Teshnehlab · Computational Intelligence and Security · 2007
The non-dominate sorting genetic algorithmic-II (NSGA-II) is a relatively recent technique for finding or approximating the Pareto-optimal set for multi-objective optimization problems. In different studies NSGA-II has shown good performance in comparison to other multi-objective evolutionary algorithms (Deb et al., 2002). In this paper an improved version which is named Niching-NSGA-II (n-NSGA-II) is proposed. This algorithm uses new method after non-dominate sorting procedure for keeping diversity. The comparison of n-NSGA-II with NSGA-II and other methods on ZDT test problems yields promising results.