1 research outputs found
Performance Evaluation of Evolutionary Algorithms for Analog Integrated Circuit Design Optimisation
An automated sizing approach for analog circuits using evolutionary
algorithms is presented in this paper. A targeted search of the search space
has been implemented using a particle generation function and a repair-bounds
function that has resulted in faster convergence to the optimal solution. The
algorithms are tuned and modified to converge to a better optimal solution with
less standard deviation for multiple runs compared to standard versions.
Modified versions of the artificial bee colony optimisation algorithm, genetic
algorithm, grey wolf optimisation algorithm, and particle swarm optimisation
algorithm are tested and compared for the optimal sizing of two operational
amplifier topologies. An extensive performance evaluation of all the modified
algorithms showed that the modifications have resulted in consistent
performance with improved convergence for all the algorithms. The
implementation of parallel computation in the algorithms has reduced run time.
Among the considered algorithms, the modified artificial bee colony
optimisation algorithm gave the most optimal solution with consistent results
across multiple runs