8 research outputs found
Flower pollination algorithm: a novel approach for multiobjective optimization
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 article, the recently developed flower pollination algorithm (FPA) is extended to solve multiobjective optimization problems. The proposed method is used to solve a set of multiobjective test functions and two bi-objective design benchmarks, and a comparison of the proposed algorithm with other algorithms has been made, which shows that the FPA is efficient with a good convergence rate. Finally, the importance for further parametric studies and theoretical analysis is highlighted and discussed
Cuckoo search: recent advances and applications
Cuckoo search (CS) is a relatively new algorithm, developed by Yang and Deb
in 2009, and CS is efficient in solving global optimization problems. In this
paper, we review the fundamental ideas of cuckoo search and the latest
developments as well as its applications. We analyze the algorithm and gain
insight into its search mechanisms and find out why it is efficient. We also
discuss the essence of algorithms and its link to self-organizing systems, and
finally we propose some important topics for further research.Comment: 9 page