Fuzzified ant colony optimization algorithm for efficient combinational circuits synthesis

With the increasing demand for high quality, more efficient, less area and less power circuits, the problem of logic circuit design has become a multiobjective optimization problem. Multiobjective optimization of logic circuits based on a fuzzified ant colony (ACO) algorithm is presented. The result...

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Bibliographic Details
Main Authors: Sarif, B.A.B., Abd-El-Barr, M., Sait, S.M., Al-Saiari, U.
Format: Conference Proceeding
Language:English
Subjects:
Ant colony optimization
Applied sciences
Artificial intelligence
Assembly
Circuit synthesis
Combinational circuits
Computer science
control theory
systems
Constraint optimization
Delay
Design engineering
Exact sciences and technology
Fuzzy logic
Logic circuits
Upper bound
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Summary:With the increasing demand for high quality, more efficient, less area and less power circuits, the problem of logic circuit design has become a multiobjective optimization problem. Multiobjective optimization of logic circuits based on a fuzzified 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.
DOI:10.1109/CEC.2004.1331049