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Nascimento,Moysés; Cruz,Cosme Damião; Peternelli,Luiz Alexandre; Campana,Ana Carolina Mota. |
The efficiency of simulated annealing algorithms and rapid chain delineation in establishing the best linkage order, when constructing genetic maps, was evaluated. Linkage refers to the phenomenon by which two or more genes, or even more molecular markers, can be present in the same chromosome or linkage group. In order to evaluate the capacity of algorithms, four F2 co-dominant populations, 50, 100, 200 and 1000 in size, were simulated. For each population, a genome with four linkage groups (100 cM) was generated. The linkage groups possessed 51, 21, 11 and 6 marks, respectively, and a corresponding distance of 2, 5, 10 and 20 cM between adjacent marks, thereby causing various degrees of saturation. For very saturated groups, with an adjacent distance... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Better order; Genetic mapping; Genomic analyses; Stochastic optimization. |
Ano: 2010 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572010000200032 |
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Lewis, Andrew; Nganje, William E.; Mattson, Jeremy W.; Miljkovic, Dragan; Wilson, William W.. |
This study provides a framework to value investment strategies to mitigate possible agro-terrorism occurrences in the food supply chain and to determine where these investments would reduce the most risk. This framework is applied to two food sectors that could be at risk: milk and green onions. Stochastic optimization is used to determine the costs and risk premiums of alternative tracking strategies. The real options method along with a portfolio of options, also referred to as the "tomato garden" framework, is used to determine where and when alternative intervention strategies should be implemented to reduce the most risk. Finally, policy implications are derived on the cost-risk tradeoffs, probability of attacks, and containment efforts if there... |
Tipo: Report |
Palavras-chave: Agro-terrorism; Stochastic optimization; Real options; Game theory; Milk; Green onions; Food Consumption/Nutrition/Food Safety. |
Ano: 2007 |
URL: http://purl.umn.edu/7630 |
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Musshoff, Oliver; Hirschauer, Norbert. |
Agricultural production relies to a great extent on biological processes in natural environments. In addition to volatile prices, it is thus heavily exposed to risks caused by the variability of natural conditions such as rainfall, temperature and pests. With a view to the apparently lacking support of risky farm production program decisions through formal planning models, the objective of this paper is to examine whether, and eventually by how much, farmers’ “intuitive” program decisions can be improved through formal statistical analyses and stochastic optimization models. In this performance comparison, we use the results of the formal planning approach that are generated in a quasi ex-ante analysis as a normative benchmark for the empirically observed... |
Tipo: Conference Paper or Presentation |
Palavras-chave: Stochastic optimization; Stochastic processes; Production risk; Program planning; Time series analysis; C1; C61; M11; Q12. |
Ano: 2008 |
URL: http://purl.umn.edu/36865 |
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Musshoff, Oliver; Hirschauer, Norbert. |
Agricultural production relies to a great extent on biological processes in natural environments. In addition to volatile prices, it is thus heavily exposed to risks caused by the variability of natural conditions such as rainfall, temperature and pests. With a view to the apparently lacking support of risky farm production program decisions through formal planning models, the objective of this paper is to examine whether, and eventually by how much, farmers’ “intuitive” program decisions can be improved through formal statistical analyses and stochastic optimization models. In this performance comparison, we use the results of the formal planning approach that are generated in a quasi ex-ante analysis as a normative benchmark for the empirically observed... |
Tipo: Conference Paper or Presentation |
Palavras-chave: Stochastic optimization; Program planning; Time series analysis; Crop Production/Industries. |
Ano: 2008 |
URL: http://purl.umn.edu/44174 |
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