Simulated annealing on uncorrelated energy landscapes
A function f:{0,1,2,L,a}n→R is said to be uncorrelated if Prob[f(x)≤u]=G(u). This paper studies the effectiveness of simulated annealing as a strategy for optimizing uncorrelated functions. A recurrence relation expressing the effectiveness of the algorithm in terms of the function G is derived. Sur...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
1994-01-01
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| Series: | International Journal of Mathematics and Mathematical Sciences |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1155/S0161171294001109 |
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| Summary: | A function f:{0,1,2,L,a}n→R is said to be uncorrelated if Prob[f(x)≤u]=G(u). This paper studies the effectiveness of simulated annealing as a strategy for optimizing uncorrelated functions. A recurrence relation expressing the effectiveness of the algorithm in terms of the function G is derived. Surprising numerical results are obtained, to the effect that for certain parametrized families of functions {Gc, c∈R}, where c represents the steepness of the curve G′(u), the effectiveness of simulated annealing increases steadily with c These results suggest that on the average annealing is effective whenever most points have very small objective function values, but a few points have very large objective function values. |
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| ISSN: | 0161-1712 1687-0425 |