A new class of optimization algorithms for circuit design and modelling
- 6 January 2003
- proceedings article
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
A class of optimization algorithms for finding the global minimum of functions of continuous variables is presented. These algorithms merge conventional local minima search strategies with the stimulated annealing (SA) technique. The rationale behind these algorithms is discussed, and a complete description is given of one of them, derived from the Hooke and Jeeves (1961) search method. Tests made on mathematical functions show an increase up to two orders of magnitudes in efficiency with respect to a conventional SA algorithm. An example of application to VLSI design is given.Keywords
This publication has 8 references indexed in Scilit:
- Minimizing multimodal functions of continuous variables with the “simulated annealing” algorithm—Corrigenda for this article is available hereACM Transactions on Mathematical Software, 1987
- A Parallel Simulated Annealing Algorithm for the Placement of Macro-CellsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 1987
- Component placement in VLSI circuits using a constant pressure Monte Carlo methodIntegration, 1985
- A general-purpose global optimizer: Implimentation and applicationsMathematics and Computers in Simulation, 1984
- Global Wiring by Simulated AnnealingIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 1983
- Optimization by Simulated AnnealingScience, 1983
- A Simplex Method for Function MinimizationThe Computer Journal, 1965
- `` Direct Search'' Solution of Numerical and Statistical ProblemsJournal of the ACM, 1961