Numerical optimization of recursive systems of equations with an application to optimal swine genetic selection

dc.contributor.advisor Jack C. M. Dekkers
dc.contributor.advisor James B. Kliebenstein
dc.contributor.advisor Wolfgang Kliemann Hawkins, Richard
dc.contributor.department Economics 2018-08-23T15:03:47.000 2020-06-30T07:21:07Z 2020-06-30T07:21:07Z Fri Jan 01 00:00:00 UTC 1999 1999
dc.description.abstract <p>A new dynamic programming method is developed for numerical optimization of recursive systems of equations, in which continuous choice variables determine the allowed choices in subsequent stages of the problem. The method works by dynamically creating bubbles, or subspaces, of the total search space, allowing the indexing of states visited for later use, and taking advantage of the fact that states adjacent to a visited state are likely to be visited. The method thereby allows search of spaces far larger than would traditionally be permitted by memory limitations. The search allows an infinite planning horizon, and tests at each stage to determine whether further optimization is worth the costs, reverting to a default choice when no longer profitable. The method is applied to the quantitative genetics problem of finding the optimal selection choices for quantitative traits using an identified locus, using the present discounted value of all generations. The method is then applied to the Estrogen Receptor Gene (ESR) to find the economic value of testing for this particular gene.</p>
dc.format.mimetype application/pdf
dc.identifier archive/
dc.identifier.articleid 13457
dc.identifier.contextkey 6804139
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath rtd/12458
dc.language.iso en
dc.source.bitstream archive/|||Fri Jan 14 19:22:03 UTC 2022
dc.subject.disciplines Agricultural Economics
dc.subject.disciplines Agriculture
dc.subject.disciplines Animal Sciences
dc.subject.disciplines Biostatistics
dc.subject.disciplines Economics
dc.subject.disciplines Genetics
dc.subject.disciplines Statistics and Probability
dc.subject.keywords Economics
dc.subject.keywords Statistics
dc.title Numerical optimization of recursive systems of equations with an application to optimal swine genetic selection
dc.type article
dc.type.genre dissertation
dspace.entity.type Publication
relation.isOrgUnitOfPublication 4c5aa914-a84a-4951-ab5f-3f60f4b65b3d dissertation Doctor of Philosophy
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