Abstract
This work describes a parallel implementation of very fast simulated reannealing (VFSR), an advanced simulated annealing method for optimization of nonlinear, multi-dimensional functions with large numbers of local minima. Parallel VFSR speed-ups on a CM-2 connection machine are reported for eight functions: De Jong's test suite, a 10-D parabolic function, and two multi-modal, highly nonlinear functions. Within the test set, the function characteristic most affecting parallel VFSR performance is the number of optimized function parameters. Low dimension functions profited least from parallelization, exhibiting speedups from 2 to 78 (where speedups are based on number of function evaluation cycles). Speed-ups for the three 10-D cost functions increased to 410, 823 and 1124. On a stochastic high dimensional (D=30) quartic cost function, the cycle ratio was over 19000. We present results of a systematic study of the dimensionality effect on three test functions. >
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