论文信息 - Automatic starting point selection for function optimization

Automatic starting point selection for function optimization

Traditional (non-stochastic) iterative methods for optimizing functions with multiple optima require a good procedure for selecting starting points. This paper illustrates how the selection of starting points can be made automatically by using a method based upon simulated annealing. We present a hybrid algorithm, possessing the accuracy of traditional routines, whilst incorporating the reliability of annealing methods, and illustrate its performance for a particularly complex practical problem.

Byron J. T. Morgan | Stephen P. Brooks | S. Brooks | B. Morgan

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