Abstract
Thanks to the success in the design of a simple sharing function, the introduction of a novel fitness assignment strategy, and the development of a new local search procedure, this paper proposes an improved evolutionary algorithm for optimal problems involving several, often conflicting objectives. The simulation results on solving a mathematical function and a prototype problem reveal that the proposed method is effective in sampling the entire Pareto-optimal front and in distributing the generated solutions over the trade-off surface.
| Original language | English |
|---|---|
| Pages (from-to) | 711-715 |
| Number of pages | 5 |
| Journal | International Journal of Applied Electromagnetics and Mechanics |
| Volume | 25 |
| Issue number | 1-4 |
| Publication status | Published - 4 Jun 2007 |
Keywords
- Evolutionary algorithm
- Multiobjective optimization
- Optimal design
- Pareto optimal
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Mechanics of Materials
- Computational Mechanics
- Physics and Astronomy (miscellaneous)