Machine-learning in optimization of expensive black-box functions

نتاج البحث: نشر في مجلةمقالةمراجعة النظراء

10 اقتباسات (Scopus)

ملخص

Modern engineering design optimization often uses computer simulations to evaluate candidate designs. For some of these designs the simulation can fail for an unknown reason, which in turn may hamper the optimization process. To handle such scenarios more effectively, this study proposes the integration of classifiers, borrowed from the domain of machine learning, into the optimization process. Several implementations of the proposed approach are described. An extensive set of numerical experiments shows that the proposed approach improves search effectiveness.

اللغة الأصليةالإنجليزيّة
الصفحات (من إلى)105-118
عدد الصفحات14
دوريةInternational Journal of Applied Mathematics and Computer Science
مستوى الصوت27
رقم الإصدار1
المعرِّفات الرقمية للأشياء
حالة النشرنُشِر - 1 مارس 2017

بصمة

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