Improving High-dimensional Simulation-driven Optimization

نتاج البحث: نشر في مجلةمقالة

ملخص

Computer simulations are being extensively used as a partial substitute for real-world experiments. Such simulations are often computationally intensive and hence metamodels are used to approximate them and to yield estimated output values more economically. While this setup can work well in low dimensional problems it can struggle in high-dimensional ones due to poor metamodel prediction accuracy. As such this study examines the application of dimensionality-reduction procedures during the search so that a simplified problems is formulated which is easier to solve and which could yield a better solution of the original one. An extensive performance analysis with both mathematical test functions and an engineering application shows the effectiveness of the proposed approach.
اللغة الأصليةإنجليزيّة أمريكيّة
الصفحات (من إلى)23-31
عدد الصفحات9
دوريةWSEAS Transactions on Information Science and Applications
مستوى الصوت17
المعرِّفات الرقمية للأشياء
حالة النشرنُشِر - 2020

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