کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
380912 | 1437469 | 2012 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Global Simplex Optimization—A simple and efficient metaheuristic for continuous optimization
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Global Simplex Optimization—A simple and efficient metaheuristic for continuous optimization Global Simplex Optimization—A simple and efficient metaheuristic for continuous optimization](/preview/png/380912.png)
چکیده انگلیسی
A new hybrid optimization algorithm is proposed for minimization of continuous multi-modal functions. The algorithm called Global Simplex Optimization (GSO) is a population set based Evolutionary Algorithm (EA) incorporating a special multi-stage, stochastic and weighted version of the reflection operator of the classical simplex method. An optional mutation operator has also been tested and then removed from the structure of the final algorithm in favor of simplicity and because of insignificant effect on performance. The promising performance achieved by GSO is demonstrated by comparisons made to some other state-of-the-art global optimization algorithms over a set of conventional benchmark problems.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Applications of Artificial Intelligence - Volume 25, Issue 1, February 2012, Pages 48–55
Journal: Engineering Applications of Artificial Intelligence - Volume 25, Issue 1, February 2012, Pages 48–55
نویسندگان
Akbar Karimi, Patrick Siarry,