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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| Format: | Article |
| Language: | English |
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Wiley
1994-01-01
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| Series: | International Journal of Mathematics and Mathematical Sciences |
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| Online Access: | http://dx.doi.org/10.1155/S0161171294001109 |
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| _version_ | 1832559834107478016 |
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| author | Ben Goertzel Malwane Ananda |
| author_facet | Ben Goertzel Malwane Ananda |
| author_sort | Ben Goertzel |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-5f2f5c084dc0438485124044bc7e5b55 |
| institution | Kabale University |
| issn | 0161-1712 1687-0425 |
| language | English |
| publishDate | 1994-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Mathematics and Mathematical Sciences |
| spelling | doaj-art-5f2f5c084dc0438485124044bc7e5b552025-02-03T01:29:09ZengWileyInternational Journal of Mathematics and Mathematical Sciences0161-17121687-04251994-01-0117479179810.1155/S0161171294001109Simulated annealing on uncorrelated energy landscapesBen Goertzel0Malwane Ananda1Department of Mathematical Sciences, University of Nevada, Las Vegas 89154, NV, USADepartment of Mathematical Sciences, University of Nevada, Las Vegas 89154, NV, USAA 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.http://dx.doi.org/10.1155/S0161171294001109simulated annealingevolutionary mutationuncorrelated functions. |
| spellingShingle | Ben Goertzel Malwane Ananda Simulated annealing on uncorrelated energy landscapes International Journal of Mathematics and Mathematical Sciences simulated annealing evolutionary mutation uncorrelated functions. |
| title | Simulated annealing on uncorrelated energy landscapes |
| title_full | Simulated annealing on uncorrelated energy landscapes |
| title_fullStr | Simulated annealing on uncorrelated energy landscapes |
| title_full_unstemmed | Simulated annealing on uncorrelated energy landscapes |
| title_short | Simulated annealing on uncorrelated energy landscapes |
| title_sort | simulated annealing on uncorrelated energy landscapes |
| topic | simulated annealing evolutionary mutation uncorrelated functions. |
| url | http://dx.doi.org/10.1155/S0161171294001109 |
| work_keys_str_mv | AT bengoertzel simulatedannealingonuncorrelatedenergylandscapes AT malwaneananda simulatedannealingonuncorrelatedenergylandscapes |