Abstract
In this letter, we integrate domain information into the original artificial bee colony algorithm to create a novel, neighborinteractive bee colony algorithm. We use the Hamming distance measure to compute variable dependency between two binary variables and employ the Gini correlation coefficient to compute variable relation between integer variables. The proposed optimization method was evaluated by minimizing binary Ising models, integer Potts models, and trapped functions. Experimental results show that the proposed method outperformed the traditional artificial bee colony and other meta-heuristics in all the testing cases.
| Original language | English |
|---|---|
| Pages (from-to) | 2034-2037 |
| Number of pages | 4 |
| Journal | IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences |
| Volume | E100A |
| Issue number | 9 |
| DOIs | |
| State | Published - Sep 2017 |
Keywords
- Artificial bee colony
- Gini correlation coefficient
- Hamming distance