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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Andradottir, S. |
| Copyright Year | 1990 |
| Description | Author affiliation: Dept. of Ind. Eng., Wisconsin Univ., Madison, WI, USA (Andradottir, S.) |
| Abstract | Classical stochastic optimization algorithms have severe problems associated with them: they converge extremely slowly on problems where the objective function is very flat, and they often diverge when the objective function is steep. The author has developed a stochastic optimization algorithm that is more robust than the older algorithms in that it is guaranteed to converge on a larger class of problems. This algorithm is guaranteed to converge even when the iterates are not assumed a priori to be bounded. This algorithm is also observed to converge faster on a significant class of problems. As the parameters can be chosen so that the new algorithm behaves very much like the older algorithms (except that it converges on a larger class of problems), this algorithm should always be used in preference to the older algorithms. |
| Starting Page | 364 |
| Ending Page | 366 |
| File Size | 267291 |
| Page Count | 3 |
| File Format | |
| ISBN | 0911801723 |
| DOI | 10.1109/WSC.1990.129542 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1990-12-09 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Stochastic processes Industrial engineering Constraint optimization H infinity control |
| Content Type | Text |
| Resource Type | Article |
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