Flower Pollination Algorithm: A Novel Approach for Multiobjective Optimization
Abstract
Multiobjective design optimization problems require multiobjective optimization techniques to solve, and it is often very challenging to obtain high-quality Pareto fronts accurately. In this paper, the recently developed flower pollination algorithm (FPA) is extended to solve multiobjective optimization problems. The proposed method is used to solve a set of multobjective test functions and two bi-objective design benchmarks, and a comparison of the proposed algorithm with other algorithms has been made, which shows that FPA is efficient with a good convergence rate. Finally, the importance for further parametric studies and theoretical analysis are highlighted and discussed.
Cite
@article{arxiv.1408.5332,
title = {Flower Pollination Algorithm: A Novel Approach for Multiobjective Optimization},
author = {Xin-She Yang and M. Karamanoglu and X. S. He},
journal= {arXiv preprint arXiv:1408.5332},
year = {2014}
}
Comments
17 pages 8 figures. arXiv admin note: substantial text overlap with arXiv:1404.0695