کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
11008030 1840487 2019 19 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Quantitative measure of nonconvexity for black-box continuous functions
ترجمه فارسی عنوان
اندازه گیری کمی از عدم غرق شدن برای عملکرد مستمر سیاه و سفید
کلمات کلیدی
تحلیل تناسب اندام تناسب اندام، متهوریستی، توابع جعبه جعبه، مشکلات بزرگ پیچیدگی، مونت کارلو انتگرال،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی
Metaheuristic algorithms usually aim to solve nonconvex optimization problems in black-box and high-dimensional scenarios. Characterizing and understanding the properties of nonconvex problems is therefore important for effectively analyzing metaheuristic algorithms and their development, improvement and selection for problem solving. This paper establishes a novel analysis framework called nonconvex ratio analysis, which can characterize nonconvex continuous functions by measuring the degree of nonconvexity of a problem. This analysis uses two quantitative measures: the nonconvex ratio for global characterization and the local nonconvex ratio for detailed characterization. Midpoint convexity and Monte Carlo integral are important methods for constructing the measures. Furthermore, as a practical feature, we suggest a rapid characterization measure that uses the local nonconvex ratio and can characterize certain black-box high-dimensional functions using a much smaller sample. Throughout this paper, the effectiveness of the proposed measures is confirmed by numerical experiments using the COCO function set.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volume 476, February 2019, Pages 64-82
نویسندگان
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