کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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6422056 | 1340607 | 2011 | 21 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: GHSÂ +Â LEM: Global-best Harmony Search using learnable evolution models GHSÂ +Â LEM: Global-best Harmony Search using learnable evolution models](/preview/png/6422056.png)
This paper presents a new optimization algorithm called GHSÂ +Â LEM, which is based on the Global-best Harmony Search algorithm (GHS) and techniques from the learnable evolution models (LEM) to improve convergence and accuracy of the algorithm. The performance of the algorithm is evaluated with fifteen optimization functions commonly used by the optimization community. In addition, the results obtained are compared against the original Harmony Search algorithm, the Improved Harmony Search algorithm and the Global-best Harmony Search algorithm. The assessment shows that the proposed algorithm (GHSÂ +Â LEM) improves the accuracy of the results obtained in relation to the other options, producing better results in most situations, but more specifically in problems with high dimensionality, where it offers a faster convergence with fewer iterations.
Journal: Applied Mathematics and Computation - Volume 218, Issue 6, 15 November 2011, Pages 2558-2578