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AIDA-CMK: Multi-Algorithm Optimization Kernel Applied to Analog IC Sizing (Paperback, 2015 ed.)
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AIDA-CMK: Multi-Algorithm Optimization Kernel Applied to Analog IC Sizing (Paperback, 2015 ed.)
Series: SpringerBriefs in Computational Intelligence
Expected to ship within 10 - 15 working days
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This work addresses the research and development of an innovative
optimization kernel applied to analog integrated circuit (IC)
design. Particularly, this works describes the modifications inside
the AIDA Framework, an electronic design automation framework fully
developed by at the Integrated Circuits Group-LX of the Instituto
de Telecomunicacoes, Lisbon. It focusses on AIDA-CMK, by enhancing
AIDA-C, which is the circuit optimizer component of AIDA, with a
new multi-objective multi-constraint optimization module that
constructs a base for multiple algorithm implementations. The
proposed solution implements three approaches to multi-objective
multi-constraint optimization, namely, an evolutionary approach
with NSGAII, a swarm intelligence approach with MOPSO and
stochastic hill climbing approach with MOSA. Moreover, the
implemented structure allows the easy hybridization between kernels
transforming the previous simple NSGAII optimization module into a
more evolved and versatile module supporting multiple single and
multi-kernel algorithms. The three multi-objective optimization
approaches were validated with CEC2009 benchmarks to constrained
multi-objective optimization and tested with real analog IC design
problems. The achieved results were compared in terms of
performance, using statistical results obtained from multiple
independent runs. Finally, some hybrid approaches were also
experimented, giving a foretaste to a wide range of opportunities
to explore in future work.
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