دانلود مقاله ISI انگلیسی شماره 46224
عنوان فارسی مقاله

الگوریتم کلونی زنبور عسل با راهبرد جستجوی متغیر برای بهینه سازی مستمر

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
46224 2015 18 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Artificial bee colony algorithm with variable search strategy for continuous optimization
منبع

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

Journal : Information Sciences, Volume 300, 10 April 2015, Pages 140–157

کلمات کلیدی
کلنی زنبور عسل مصنوعی - بهینه سازی مستمر - راهبرد جستجو - انتگرال گیری
پیش نمایش مقاله
پیش نمایش مقاله الگوریتم کلونی زنبور عسل با راهبرد جستجوی متغیر برای بهینه سازی مستمر

چکیده انگلیسی

The artificial bee colony (ABC) algorithm is a swarm-based optimization technique proposed for solving continuous optimization problems. The artificial agents of the ABC algorithm use one solution update rule during the search process. To efficiently solve optimization problems with different characteristics, we propose the integration of multiple solution update rules with ABC in this study. The proposed method uses five search strategies and counters to update the solutions. During initialization, each update rule has a constant counter content. During the search process performed by the artificial agents, these counters are used to determine the rule that is selected by the bees. Because the optimization problems and functions have different characteristics, one or more search strategies are selected and are used during the iterations according to the characteristics of the numeric functions in the proposed approach. By using the search strategies and mechanisms proposed in the present study, the artificial agents learn which update rule is more appropriate based on the characteristics of the problem to find better solutions. The performance and accuracy of the proposed method are examined on 28 numerical benchmark functions, and the obtained results are compared with various classical versions of ABC and other nature-inspired optimization algorithms. The experimental results show that the proposed algorithm, integrated and improved with search strategies, outperforms the basic variants and other variants of the ABC algorithm and other methods in terms of solution quality and robustness for most of the experiments.

خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.