کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6747559 | 505376 | 2016 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Perfiles de comportamiento numérico de los métodos de búsqueda immune network algorithm y bacterial foraging optimization algorithm en funciones benchmark
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی خودرو
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
This paper reports the application of the performance profiles model comparing the numerical methods Immune Network (AiNet) and Bacterial Foraging Optimization Algorithm (BFOA) in 18 benchmark optimization functions. Specifically robustness, efficiency and execution time of these methods were compared in search spaces with local minima multiple, bowl-shaped, plate-shaped, valley-shaped, steep ridges and other known optimization functions as styblinski-tang and beale function. The results show that the method AiNet (Castro et al., 2002) is more robust than the BFOA method (Passino, 2010) for the case studies considered in this work. However there are differences in the efficiency (number of evaluated functions and convergence time) between both methods. BFOA is the algorithm with best perform in terms of the number of evaluated functions.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: IngenierÃa, Investigación y TecnologÃa - Volume 17, Issue 4, OctoberâDecember 2016, Pages 479-490
Journal: IngenierÃa, Investigación y TecnologÃa - Volume 17, Issue 4, OctoberâDecember 2016, Pages 479-490
نویسندگان
RÃos-Willars Ernesto, Liñán-GarcÃa Ernesto, Batres Rafael, Garza-GarcÃa Yolanda,