دانلود مقاله ISI انگلیسی شماره 78810
ترجمه فارسی عنوان مقاله

یک الگوریتم تکاملی ترکیبی برای نقشه برداری منطق تحمل تنوع چند هدفه در معماری دروازه مقیاس نانو

عنوان انگلیسی
A hybrid evolutionary algorithm for multiobjective variation tolerant logic mapping on nanoscale crossbar architectures
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
78810 2016 12 صفحه PDF
منبع

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

Journal : Applied Soft Computing, Volume 38, January 2016, Pages 955–966

ترجمه کلمات کلیدی
تیر افقی دروازه در مقیاس نانو؛ نقشه برداری منطق تحمل تنوع؛ بهینه سازی چندمنظوره دوسطحی؛ برنامه ریزی خطی مبتنی بر مجارستان؛ الگوریتم تکاملی ترکیبی
کلمات کلیدی انگلیسی
Nanoscale crossbar; Variation tolerant logic mapping; Bilevel multiobjective optimization; Hungarian-based linear programming; Hybrid evolutionary algorithm
پیش نمایش مقاله
پیش نمایش مقاله  یک الگوریتم تکاملی ترکیبی برای نقشه برداری منطق تحمل تنوع چند هدفه در معماری دروازه مقیاس نانو

چکیده انگلیسی

Nanoscale crossbar architectures have received steadily growing interests as a result of their great potential to be main building blocks in nanoelectronic circuits. However, due to the extremely small size of nanodevices and the bottom-up self-assembly nanofabrication process, considerable process variation will be an inherent vice for crossbar nanoarchitectures. In this paper, the variation tolerant logical mapping problem is treated as a bilevel multiobjective optimization problem. Since variation mapping is an NP-complete problem, a hybrid multiobjective evolutionary algorithm is designed to solve the problem adhering to a bilevel optimization framework. The lower level optimization problem, most frequently tackled, is modeled as the min–max-weight and min-weight-gap bipartite matching (MMBM) problem, and a Hungarian-based linear programming (HLP) method is proposed to solve MMBM in polynomial time. The upper level optimization problem is solved by evolutionary multiobjective optimization algorithms, where a greedy reassignment local search operator, capable of exploiting the domain knowledge and information from problem instances, is introduced to improve the efficiency of the algorithm. The numerical experiment results show the effectiveness and efficiency of proposed techniques for the variation tolerant logical mapping problem.