Name
Abstract | ||
|---|---|---|
Considering that the invasive weed optimization (IWO) algorithm and the harmony search (HS) algorithm are inclined to fall into local optima with low convergence precision when they are used to deal with complex function optimization problems, this paper proposes a hybrid algorithm, HS-IWO algorithm, which is combined HS algorithm and IWO algorithm. We introduce strategies such as fixing the number of seeds, reinitializing limit solutions, multi-individual global HS, parameter optimization, etc. In order to make the two algorithms take advantage of their merits, they are mixed organically in this paper. Through tests on some complex functions of benchmark, the experimental results display that the HS-IWO algorithm has the efficiency and robustness of the algorithms. It is an optimization algorithm that is highly effective and stable, especially to be applied to the optimization of complicated functions compared with other intelligent optimization algorithms. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1142/S0218001418590061 | INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE |
Keywords | Field | DocType |
IWO algorithm, HS algorithm, multi-individual, mixed mechanism, HS-IWO | Convergence (routing),Mathematical optimization,Hybrid algorithm,Global optimization,Local optimum,Meta-optimization,Multi-swarm optimization,Artificial intelligence,Harmony search,HS algorithm,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
32 | 4 | 0218-0014 |
Citations | PageRank | References |
2 | 0.36 | 19 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aijia Ouyang | 1 | 159 | 19.34 |
| Shuo Peng | 2 | 5 | 1.08 |
| Xuyu Peng | 3 | 7 | 3.13 |
| Qian Wang | 4 | 245 | 55.19 |