A STOCHASTIC METHOD FOR GLOBAL OPTIMIZATION

A stochastic method for global optimization is described and evaluated. The method involves a combination of sampling, clustering and local search, and terminates with a range of confidence intervals on the value of the global optimum. Computational results on standard test functions are included as well.


Issue Date:
1980
Publication Type:
Working or Discussion Paper
DOI and Other Identifiers:
Record Identifier:
https://ageconsearch.umn.edu/record/272200
Language:
English
Total Pages:
23
Series Statement:
REPORT 8001 /0




 Record created 2018-04-26, last modified 2020-10-28

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