Symbolic analysis of large analog circuits with determinant decision diagrams
ICCAD '97 Proceedings of the 1997 IEEE/ACM international conference on Computer-aided design
Circuit complexity reduction for symbolic analysis of analog integrated circuits
Proceedings of the 36th annual ACM/IEEE Design Automation Conference
Practical synthesis of high-performance analog circuits
Practical synthesis of high-performance analog circuits
Convergence of the simulated annealing algorithm for continuous global optimization
Journal of Optimization Theory and Applications
Conditions for the convergence of evolutionary algorithms
Journal of Systems Architecture: the EUROMICRO Journal - Special issue on evolutionary computing
On the Convergence of Pattern Search Algorithms
SIAM Journal on Optimization
Journal of Global Optimization
Analog Circuit Sizing Using Adaptive Worst-Case Parameter Sets
Proceedings of the conference on Design, automation and test in Europe
On the Convergence of a Population-Based Global Optimization Algorithm
Journal of Global Optimization
A combined heuristic optimization technique
Advances in Engineering Software - Special issue on evolutionary optimization of engineering problems
A Combined Global & Local Search (CGLS) Approach to Global Optimization
Journal of Global Optimization
Evolutionary programming made faster
IEEE Transactions on Evolutionary Computation
An evolutionary approach to automatic synthesis of high-performance analog integrated circuits
IEEE Transactions on Evolutionary Computation
Sample-sort simulated annealing
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Synthesis of high-performance analog circuits in ASTRX/OBLX
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Anaconda: simulation-based synthesis of analog circuits via stochastic pattern search
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Study of multiscale global optimization based on parameter space partition
Journal of Global Optimization
An augmented Lagrangian fish swarm based method for global optimization
Journal of Computational and Applied Mathematics
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This paper presents a new hybrid global optimization method referred to as DESA. The algorithm exploits random sampling and the metropolis criterion from simulated annealing to perform global search. The population of points and efficient search strategy of differential evolution are used to speed up the convergence. The algorithm is easy to implement and has only a few parameters. The theoretical global convergence is established for the hybrid method. Numerical experiments on 23 mathematical test functions have shown promising results. The method was also integrated into SPICE OPUS circuit simulator to evaluate its practical applicability in the area of analog integrated circuit sizing. Comparison was made with basic simulated annealing, differential evolution, and a multistart version of the constrained simplex method. The latter was already a part of SPICE OPUS and produced good results in past research.