دانلود مقاله ISI انگلیسی شماره 46289
ترجمه فارسی عنوان مقاله

مجازات تطبیقی و عملکرد مانع بر اساس منطق فازی

عنوان انگلیسی
Adaptive Penalty and Barrier function based on Fuzzy Logic
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
46289 2015 7 صفحه PDF
منبع

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

Journal : Expert Systems with Applications, Volume 42, Issue 19, 1 November 2015, Pages 6777–6783

ترجمه کلمات کلیدی
نرم افزار - برنامه ریزی ریاضی فازی - ریاضیات - بهینه سازی مشتق - روش مستقیم جستجو - منطق فازی
کلمات کلیدی انگلیسی
Applications; Fuzzy mathematical programming; Mathematics; Derivative free optimization; Direct search methods; Penalty and Barrier functions; Fuzzy Logic
پیش نمایش مقاله
پیش نمایش مقاله  مجازات تطبیقی و عملکرد مانع بر اساس منطق فازی

چکیده انگلیسی

Optimization methods have been used in many areas of knowledge, such as Engineering, Statistics, Chemistry, among others, to solve optimization problems. In many cases it is not possible to use derivative methods, due to the characteristics of the problem to be solved and/or its constraints, for example if the involved functions are non-smooth and/or their derivatives are not know. To solve this type of problems a Java based API has been implemented, which includes only derivative-free optimization methods, and that can be used to solve both constrained and unconstrained problems. For solving constrained problems, the classic Penalty and Barrier functions were included in the API. In this paper a new approach to Penalty and Barrier functions, based on Fuzzy Logic, is proposed. Two penalty functions, that impose a progressive penalization to solutions that violate the constraints, are discussed. The implemented functions impose a low penalization when the violation of the constraints is low and a heavy penalty when the violation is high. Numerical results, obtained using twenty-eight test problems, comparing the proposed Fuzzy Logic based functions to six of the classic Penalty and Barrier functions are presented. Considering the achieved results, it can be concluded that the proposed penalty functions besides being very robust also have a very good performance.