Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6855659 | Expert Systems with Applications | 2016 | 8 Pages |
Abstract
Nature-inspired meta-heuristics have gained popularity for the solution of many real world complex problems, and the artificial bee colony algorithm is one of the most powerful optimisation methods among the meta-heuristics. However, a major drawback prevents the artificial bee colony algorithm from accurately and efficiently finding final solutions for complex problems, whose variables interact with each other. We propose a novel optimization method based on the artificial bee colony algorithm and statistics. The proposed optimization method is evaluated for Pott models and optimization linkage functions, and the proposed method is verified to outperform traditional artificial bee colony and other meta-heuristics for those cases.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Phuc Nguyen Hong, Chang Wook Ahn,