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Fuzzified Ant Colony Optimization Algorithm for Efficient Combinational Circuits Synthesis

机译:高效组合电路综合的模糊化蚁群优化算法

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摘要

Abstract- With the increasing demand for high quality, more efficient, less areaand less power circuits, the problem of logic circuit design has become a multiobjective optimization problem. In this paper, multiobjective optimization of logic circuits based on a fnzzified Ant Colony (ACO) algorithm is presented. The results obtained using the proposed algorithm are compared to those obtained using SIS in terms of area, delay and power for some known circuits. It is shown that the circuits produced by the proposed algorithm are better as compared to those obtained by SIS.
机译:摘要-随着对高质量,更高效,更小面积和更少电源电路的需求的不断增长,逻辑电路设计问题已成为多目标优化问题。本文提出了一种基于模糊蚁群算法的逻辑电路多目标优化方法。对于某些已知电路,将使用该算法获得的结果与使用SIS获得的结果在面积,延迟和功率方面进行了比较。结果表明,与SIS算法相比,该算法产生的电路更好。

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