| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 6856242 | Information Sciences | 2018 | 22 Pages |
Abstract
In this paper, a Maximum A Posteriori (MAP) principle based rule is proposed to palliate the operators' selection problem for solving different kinds of continuous optimization problems. This learning based approach allows switching between different strategies during the optimization. This algorithm is called Maximum a posteriori based Evolutionary Algorithm (MEA). Experimental analysis was performed and proved its efficiency and robustness on a large set of 34 problems.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Asmaa Ghoumari, Amir Nakib, Patrick Siarry,