Improving the non-dominate sorting genetic algorithm for multi-objective optimization
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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.
| Original language | English |
|---|---|
| Title of host publication | 2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007) |
| Pages | 89-92 |
| Number of pages | 4 |
| Publication status | Published - 2007 |
| Externally published | Yes |