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Economic analysis of optimal product...

Li, Ning.

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Economic analysis of optimal production and marketing management strategies for swine production operations with PayleanRTM.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Economic analysis of optimal production and marketing management strategies for swine production operations with PayleanRTM./
作者:	Li, Ning.
面頁冊數:	258 p.
附註:	Source: Dissertation Abstracts International, Volume: 64-11, Section: A, page: 4141.
Contained By:	Dissertation Abstracts International64-11A.
標題:	Economics, Agricultural. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3113833
ISBN:	9780496613267

Economic analysis of optimal production and marketing management strategies for swine production operations with PayleanRTM.
Li, Ning.

Economic analysis of optimal production and marketing management strategies for swine production operations with PayleanRTM. - 258 p.

Source: Dissertation Abstracts International, Volume: 64-11, Section: A, page: 4141.

Thesis (Ph.D.)--Purdue University, 2003.

With increasing competitive pressure and scale of operations, livestock businesses require efficient management decisions. The purpose of this research was to combine state of the art biological swine growth model with economic optimization principles so as to develop a modeling system that can be used to fine tune the management of modern swine production operations. This modeling system can be calibrated to a wide range of production and marketing systems, making it a useful tool for developing strategies that are specific to a producer's operation.

ISBN: 9780496613267Subjects--Topical Terms:

626648
Economics, Agricultural.

Economic analysis of optimal production and marketing management strategies for swine production operations with PayleanRTM.
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245 1 0 $a Economic analysis of optimal production and marketing management strategies for swine production operations with PayleanRTM.
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500 $a Source: Dissertation Abstracts International, Volume: 64-11, Section: A, page: 4141.
500 $a Co-Major Professors: Kenneth A. Foster; Paul V. Preckel.
502 $a Thesis (Ph.D.)--Purdue University, 2003.
520 $a With increasing competitive pressure and scale of operations, livestock businesses require efficient management decisions. The purpose of this research was to combine state of the art biological swine growth model with economic optimization principles so as to develop a modeling system that can be used to fine tune the management of modern swine production operations. This modeling system can be calibrated to a wide range of production and marketing systems, making it a useful tool for developing strategies that are specific to a producer's operation.
520 $a The specific goals of this research included: (1) to determine optimal production and marketing management strategies for dietary Paylean (both constant and varying concentration programs) and lysine concentrations under alternative phase-feeding programs, growth conditions and payment systems, either for a single hog with average growth properties or a herd of pigs; (2) to investigate the impact of economic conditions on management strategies; (3) to determine differences between economically optimal management strategies when simulation focuses at the herd level rather than on the herd average.
520 $a A key feature of this research was the more precise modeling of the economic objective function. In particular, payment grids common in the pork packing industry are incorporated into the model directly, resulting in a discontinuous objective function for the optimization of returns. A grid search is used to maximize this nonconcave objective. Therefore, the simulated scenarios can reflect the true conditions facing a swine producer.
520 $a An innovation of the research was to use a stochastic growth model to investigate the production management strategies at the herd level. The stochastic growth model gets its name from two features: stochastic live weight growth and stochastic carcass component growth. Each individual pig has its own live weight and carcass component growth curve, which together approximately reproduce the mean and covariance structure of the genetic population. Thus, the stochastic model has broad applications for the hog industry and implications for future economic research on livestock production.
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