STOCHASTIC GLOBAL OPTIMIZATION METHODS PART I: CLUSTERING METHODS

In this stochastic approach to global optimization, clustering techniques are applied to identify local minima of a real valued objective function that are potentially global. Three different methods of this type are described; their accuracy and efficiency are analyzed in detail.


Issue Date:
1985
Publication Type:
Working or Discussion Paper
DOI and Other Identifiers:
Record Identifier:
https://ageconsearch.umn.edu/record/272329
Language:
English
Total Pages:
49
Series Statement:
REPORT 8539/A




 Record created 2018-04-30, last modified 2020-10-28

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