کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6905255 | 862813 | 2015 | 24 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Multi-population differential evolution with balanced ensemble of mutation strategies for large-scale global optimization
ترجمه فارسی عنوان
تکامل متفرقه جمعیتی با مجموعه ای متعادل از استراتژی های جهش برای بهینه سازی جهانی در مقیاس بزرگ
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کلمات کلیدی
تکامل دیفرانسیل، بهینه سازی در مقیاس بزرگ، استراتژی جهش د، مقیاس پذیری،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
Differential evolution (DE) is a simple, yet very effective, population-based search technique. However, it is challenging to maintain a balance between exploration and exploitation behaviors of the DE algorithm. In this paper, we boost the population diversity while preserving simplicity by introducing a multi-population DE to solve large-scale global optimization problems. In the proposed algorithm, called mDE-bES, the population is divided into independent subgroups, each with different mutation and update strategies. A novel mutation strategy that uses information from either the best individual or a randomly selected one is used to produce quality solutions to balance exploration and exploitation. Selection of individuals for some of the tested mutation strategies utilizes fitness-based ranks of these individuals. Function evaluations are divided into epochs. At the end of each epoch, individuals between the subgroups are exchanged to facilitate information exchange at a slow pace. The performance of the algorithm is evaluated on a set of 19 large-scale continuous optimization problems. A comparative study is carried out with other state-of-the-art optimization techniques. The results show that mDE-bES has a competitive performance and scalability behavior compared to the contestant algorithms.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Soft Computing - Volume 33, August 2015, Pages 304-327
Journal: Applied Soft Computing - Volume 33, August 2015, Pages 304-327
نویسندگان
Mostafa Z. Ali, Noor H. Awad, Ponnuthurai N. Suganthan,