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SOLUTION EFFICIENCY OF GENETIC ALGORITHM APPLICATIONS
SOLUTION EFFICIENCY OF GENETIC ALGORITHM APPLICATIONS
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机译：遗传算法应用的求解效率
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摘要
A method of optimizing a very large scale integrated circuit design takes a circuit description which includes interconnected circuit components and characteristic variables assigned to the circuit components such as environmental, operational or process parameters, computes a first solution for the characteristic variables using a statistical analysis, and then computes a second solution for the characteristic variables using an evolutionary analysis seeded by the first solution. In the exemplary implementation the statistical analysis is a central composite design (CCD) and the evolutionary analysis is a genetic algorithm. Best case and worst case CCD solutions may be used to seed separate genetic algorithm runs and derive global best case and global worst case solutions. These solutions may be compared for sensitivity analysis. The method thereby provides significant reduction in time-to-solution with accurate simulation results.
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