کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5471385 | 1519392 | 2017 | 27 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Improved biogeography-based optimization with random ring topology and Powell's method
ترجمه فارسی عنوان
بهبود بهینه سازی مبتنی بر بیوگرافی با توپولوژی تصادفی و روش پائول
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کلمات کلیدی
بهینه سازی مبتنی بر بیوگرافی، روش پائول، توپولوژی حلقه تصادفی، کلنی زنبور عسل مصنوعی،
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مکانیک محاسباتی
چکیده انگلیسی
Biogeography-based optimization (BBO) is a competitive population optimization algorithm based on biogeography theory with inherently insufficient exploration capability and slow convergence speed. To overcome limitations, we propose an improved variant of BBO, named PRBBO, for solving global optimization problems. In PRBBO, a hybrid migration operator with random ring topology, a modified mutation operator, and a self-adaptive Powell's method are rational integrated together. The hybrid migration operator with random ring topology, denoted as RMO, is created by using local ring topology to replace global topology, which can avoid the asymmetrical migration operation and enhance potential population diversity. The self-adaptive Powell's method is amended by using self-adaptive parameters for suiting evolution process to enhance solution precision quickly. Extensive experimental tests are carried out on 24 benchmark functions to show effectiveness of the proposed algorithm. Simulation results were compared with original BBO, ABC, DE, other variants of the BBO, and other state-of-the-art evolutionary algorithms. Finally, the effectiveness of operators on the performance of PRBBO is also discussed.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Mathematical Modelling - Volume 41, January 2017, Pages 630-649
Journal: Applied Mathematical Modelling - Volume 41, January 2017, Pages 630-649
نویسندگان
Feng Quanxi, Liu Sanyang, Zhang Jianke, Yang Guoping, Yong Longquan,