Name
Title | ||
|---|---|---|
A Hybrid Algorithm Based On Bat-Inspired Algorithm And Differential Evolution For Constrained Optimization Problems |
Abstract | ||
|---|---|---|
How to solve constrained optimization problems (COPs) is a significant research issue and we combine the bat-inspired algorithm (BA) with differential evolution (DE) into a new hybrid algorithm called BA-DE for solving the COPs. Traditional BAs are prone to sink into stagnation or local optima when no bat individual founds a better location than the past locations for several generations. DE is adopted for updating the past location of bat individuals to force BA to jump out of stagnation or local optima, since it has a great local searching capability. The performance of BA-DE algorithm is improved by the proposed hybrid mechanism. We use 24 well-known benchmark functions to verify the overall performance of our proposed algorithm. Comparisons show that BA-DE outperforms most advanced methods in terms of the final solution's quality. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1142/S0218001415590077 | INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE |
Keywords | Field | DocType |
Bat-inspired algorithm, BA-DE, constrained optimization, constraint-handling method, differential evolution | Mathematical optimization,Hybrid algorithm,Local optimum,Algorithm,Differential evolution,Artificial intelligence,Constrained optimization problem,Jump,Mathematics,Machine learning,Constrained optimization | Journal |
Volume | Issue | ISSN |
29 | 4 | 0218-0014 |
Citations | PageRank | References |
8 | 0.52 | 22 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shengyu Pei | 1 | 9 | 1.22 |
| Aijia Ouyang | 2 | 159 | 19.34 |
| Lang Tong | 3 | 5677 | 559.91 |