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Operations Research, Systems Engineering and Industrial Engineering Commons

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Iowa State University

Operational Research

Optimization

Articles 1 - 3 of 3

Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Optimizing Selection And Mating In Genomic Selection With A Look-Ahead Approach: An Operations Research Framework, Saba Moeinizade, Guiping Hu, Lizhi Wang, Patrick Schnable Jul 2019

Optimizing Selection And Mating In Genomic Selection With A Look-Ahead Approach: An Operations Research Framework, Saba Moeinizade, Guiping Hu, Lizhi Wang, Patrick Schnable

Industrial and Manufacturing Systems Engineering Publications

New genotyping technologies have made large amounts of genotypic data available for plant breeders to use in their efforts to accelerate the rate of genetic gain. Genomic selection (GS) techniques allow breeders to use genotypic data to identify and select, for example, plants predicted to exhibit drought tolerance, thereby saving expensive and limited field-testing resources relative to phenotyping all plants within a population. A major limitation of existing GS approaches is the trade-off between short-term genetic gain and long-term potential. Some approaches focus on achieving short-term genetic gain at the cost of reduced genetic diversity necessary for long-term gains. In ...


Three New Approaches To Genomic Selection, Lizhi Wang, Guodong Zhu, Will Johnson, Mriga Kher Jan 2018

Three New Approaches To Genomic Selection, Lizhi Wang, Guodong Zhu, Will Johnson, Mriga Kher

Industrial and Manufacturing Systems Engineering Publications

Conventional genomic selection approaches use breeding values to evaluate individual plants or animals and to make selection decisions. Multiple variants of breeding values and selection approaches have been proposed, but they suffer two major limitations. First, selection decisions are not responsive to changes in time and resource availability. Second, selection decisions are not coordinated with related decisions such as mating and resource allocation. We present three new genomic selection approaches that attempt to address these two limitations, which were designed by engineering students in a class project at Iowa State University. Compared with previous approaches using the same data set ...


Three Essays On Multi-Level Optimization Models And Applications, Mohammad Rahdar Jan 2016

Three Essays On Multi-Level Optimization Models And Applications, Mohammad Rahdar

Graduate Theses and Dissertations

The general form of a multi-level mathematical programming problem is a set of nested optimization problems, in which each level controls a series of decision variables independently. However, the value of decision variables may also impact the objective function of other levels. A two-level model is called a bilevel model and can be considered as a Stackelberg game with a leader and a follower. The leader anticipates the response of the follower and optimizes its objective function, and then the follower reacts to the leader's action.

The multi-level decision-making model has many real-world applications such as government decisions, energy ...