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An Improved Artificial Bee Colony Algorithm for Solving Optimization Problems
| Content Provider | Semantic Scholar |
|---|---|
| Author | Wang, Chun-Feng Zhang, Yonghong |
| Copyright Year | 2016 |
| Abstract | The artificial bee colony (ABC) algorithm is a simple and effective optimization algorithm that can be applied to solve many real-world optimization problems. In this paper, an improved artificial bee colony algorithm, named IABC, is proposed. In this algorithm, a new search equation for onlooker bees is presented, in which the optimal and sub-optimal solutions are considered in the iteration process. In addition, for enhancing the global convergence, the initial population are generated by using a chaotic system and an opposition-based method. Furthermore, for improving the global convergence speed of our algorithm, a chaotic search is adopted in the best solution of the current iteration. Experimental results tested on 20 benchmark functions show that the IABC algorithm is far better than the basic ABC algorithm and other three improved ABC algorithms on the tested problems. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.iaeng.org/IJCS/issues_v43/issue_3/IJCS_43_3_09.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
