دانلود مقاله ISI انگلیسی شماره 78894
عنوان فارسی مقاله

معادله ها و تفاوت های الگوریتم های تکاملی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
78894 2013 11 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
On the equivalences and differences of evolutionary algorithms
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Engineering Applications of Artificial Intelligence, Volume 26, Issue 10, November 2013, Pages 2397–2407

کلمات کلیدی
الگوریتم های تکاملی؛ الگوریتم ژنتیک؛ بهینه سازی مبتنی بر جغرافیای زیستی؛ تکامل تفاضلی؛ استراتژی تکامل؛ بهینه سازی ازدحام ذرات
پیش نمایش مقاله
پیش نمایش مقاله معادله ها و تفاوت های الگوریتم های تکاملی

چکیده انگلیسی

Evolutionary algorithms (EAs) are fast and robust computation methods for global optimization, and have been widely used in many real-world applications. We first conceptually discuss the equivalences of various popular EAs including genetic algorithm (GA), biogeography-based optimization (BBO), differential evolution (DE), evolution strategy (ES) and particle swarm optimization (PSO). We find that the basic versions of BBO, DE, ES and PSO are equal to the GA with global uniform recombination (GA/GUR) under certain conditions. Then we discuss their differences based on biological motivations and implementation details, and point out that their distinctions enhance the diversity of EA research and applications. To further study the characteristics of various EAs, we compare the basic versions and advanced versions of GA, BBO, DE, ES and PSO to explore their optimization ability on a set of real-world continuous optimization problems. Empirical results show that among the basic versions of the algorithms, BBO performs best on the benchmarks that we studied. Among the advanced versions of the algorithms, DE and ES perform best on the benchmarks that we studied. However, our main conclusion is that the conceptual equivalence of the algorithms is supported by the fact that algorithmic modifications result in very different performance levels.

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