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| Content Provider | IET Digital Library |
|---|---|
| Author | Cao, Yongcun Ji, Saisai Lu, Yong |
| Abstract | The artificial bee colony (ABC) algorithm is a biological-inspired optimisation algorithm proposed by Karaboga. Since its solution search equation is good at exploration but poor at exploitation, the ABC algorithm converges slowly and is easy to fall into local optimum. Inspired by opposition-based learning (OBL), the authors propose an improved ABC algorithm called opposition-based learning ABC (OLABC). In OLABC, firstly, the population would be initialised using OBL. Secondly, to ensure the diversity of the population during the iterative process, the solution search equation is employed to bee phase would be improved. Generate the opposite solution when the fitness value of the newly generated solution is smaller than the current solution, and then apply the greedy selection strategy to update the solution. Thirdly, the adaptive weight strategy is used to dynamically adjust the weight, balancing the global exploration and local exploitation capabilities of the algorithm. Experiments on a set of benchmark functions show that OLABC has better convergence speed and optimisation precision than the compared algorithms. |
| Starting Page | 3639 |
| Ending Page | 3650 |
| Page Count | 12 |
| ISSN | 17519659 |
| Volume Number | 14 |
| e-ISSN | 17519667 |
| Issue Number | Issue 15, Dec (2020) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2020.0111 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-ipr/14/15 |
| Journal | IET Image Processing |
| Publisher Date | 2020-06-19 |
| Access Restriction | Open |
| Rights Holder | © The Institution of Engineering and Technology |
| Subject Keyword | ABC Algorithm Adaptive Weight Strategy Artificial Bee Colony Algorithm Bee Phase Biological-inspired Optimisation Algorithm Convergence Global Exploration Greedy Algorithm Greedy Selection Strategy Interpolation And Function Approximation Iterative Method Iterative Process Learning in AI Local Exploitation Capabilities Numerical Analysis OBL OLABC Opposition-based Learning ABC Optimisation Optimisation Technique Search Problem Solution Search Equation |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software |
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