Evolutionary programming as a solution technique for the Bellman equation
Paul Gomme ()
No 9816, Working Papers (Old Series) from Federal Reserve Bank of Cleveland
Evolutionary programming is a stochastic optimization procedure that has proved useful in optimizing difficult functions. This paper shows that evolutionary programming can be used to solve the Bellman equation problem with a high degree of accuracy and substantially less CPU time than Bellman equation iteration. Future applications will focus on sometimes binding constraints, a class of problem for which standard solutions techniques are not applicable.
Keywords: Econometric models; Programming (Mathematics) (search for similar items in EconPapers)
Date: 1998, Revised 1998
New Economics Papers: this item is included in nep-cmp and nep-dge
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed
Downloads: (external link)
https://www.clevelandfed.org/~/media/content/newsr ... ique%20pdf.pdf?la=en Full text (application/pdf)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:fip:fedcwp:9816
Ordering information: This working paper can be ordered from
Access Statistics for this paper
More papers in Working Papers (Old Series) from Federal Reserve Bank of Cleveland Contact information at EDIRC.
Bibliographic data for series maintained by ().