Population Ranking Based Differential evolution with Simulated Annealing for Circuit Optimization

Jernej Olenšek, Árpád Bűrmen


Finding the values of circuit parameters for which the resulting circuit satisfies the design requirements can be formulated as an optimization problem. This problem is often solved using global optimization algorithms that provide some guarantee the resulting solution is the best possible one provided that the algorithm is given sufficient time. Unfortunately, these algorithms are slow and require many circuit evaluations. One of the algorithms proposed in our past research is PSADE that combines the favorable properties of simulated annealing and differential evolution and was shown to be a fast and reliable tool for solving circuit optimization problems. To make PSADE faster we replace the Metropolis criterion for accepting a trial point with one that is based on population ranking. The proposed algorithm retains its highly parallel nature. We tested the algorithm on a set of mathematical test functions and on a real-world circuit optimization problem. The results show the modified algorithm is on average two times faster than PSADE on circuit design problems.


differential evolution; simulated annealing; population ranking; global optimization; circuit design

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