کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6892807 | 699180 | 2016 | 21 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Computational investigation of simple memetic approaches for continuous global optimization
ترجمه فارسی عنوان
بررسی محاسباتی روشهای ساده مامیتی برای بهینه سازی جهانی مداوم
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کلمات کلیدی
بهینه سازی جهانی، رویکردهای ممتازی، مناظر کانال،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
چکیده انگلیسی
In Locatelli et al. (2014) [20] a memetic approach, called MDE (Memetic Differential Evolution), for the solution of continuous global optimization problems, has been introduced and proved to be quite efficient in spite of its simplicity. In this paper we computationally investigate some variants of MDE. The investigation reveals that the best tested variant of MDE outperforms the original MDE itself, but also that the best variant depends on some properties of the function to be optimized. In particular, a greedy variant of MDE turns out to perform very well over functions with a single-funnel landscape, while another variant, based on a diversity measure applied to the members of the population, works better over functions with a multi-funnel landscape. A hybrid approach is also proposed which combines both the previous variants in order to obtain an overall performance which is good over all functions.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Operations Research - Volume 72, August 2016, Pages 50-70
Journal: Computers & Operations Research - Volume 72, August 2016, Pages 50-70
نویسندگان
Federico Cabassi, Marco Locatelli,