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Preemptive linear goal programming in optimal two-crop succession farming system of financed Kapatagan farmers / Richard Egos Tabaranza.

By: Material type: TextTextLanguage: English Publication details: 2006Description: 115 leavesSubject(s): Dissertation note: Thesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2002 Abstract: The Preemptive Linear Goal Programming (LGP) demonstrated its efficacy in analyzing the data of financed farmers in Kapatagan. The actualized model procured feasible land allocations to six major crops namely: cabbage, Chinese cabbage, corn, tomato, potato, and carrot planted following a two-crop succession system. The study considered two different hierarchies of objectives from farmers. The first hierarchy manifested the importance of maximizing the net income as well as minimizing the working capital. The model has exhausted optimal land allocations from 115 feasible two-crop successions that could achieve the aspired objectives of the farmers as nearly as possible. The study reckoned with a one hectare land area available for crop production that the model responded efficiently. The second hierarchy pertained to the emphasis of the importance of the family labor workforce in the objectives. The model established the means to fully reach the objective of maximizing the family labor workforce of the farmers. As a result, additional labor was minimized, in effect of the full utilization of family labor resource. The actual application of NPK fertilizer was determined to be excessive while application of organic matter was strongly suggested by the results of this study. The model has also confirmed that the capital fixed to PhP40,000.00 for one year was insufficient for cop production. With the capabilities of LGP model in ensuring a close distance from the desired objective, the farmer can set forth sound decisions regarding the allocation of land to efficiently utilize their available resources in farming.
List(s) this item appears in: BS Applied Mathematics
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Cover image Item type Current library Collection Call number Status Date due Barcode
University Library Theses Room-Use Only LG993.5 2006 A64 T33 (Browse shelf(Opens below)) Not For Loan 3UPML00011622
University Library Archives and Records Preservation Copy LG993.5 2006 A64 T33 (Browse shelf(Opens below)) Not For Loan 3UPML00021974

Thesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2002

The Preemptive Linear Goal Programming (LGP) demonstrated its efficacy in analyzing the data of financed farmers in Kapatagan. The actualized model procured feasible land allocations to six major crops namely: cabbage, Chinese cabbage, corn, tomato, potato, and carrot planted following a two-crop succession system. The study considered two different hierarchies of objectives from farmers. The first hierarchy manifested the importance of maximizing the net income as well as minimizing the working capital. The model has exhausted optimal land allocations from 115 feasible two-crop successions that could achieve the aspired objectives of the farmers as nearly as possible. The study reckoned with a one hectare land area available for crop production that the model responded efficiently. The second hierarchy pertained to the emphasis of the importance of the family labor workforce in the objectives. The model established the means to fully reach the objective of maximizing the family labor workforce of the farmers. As a result, additional labor was minimized, in effect of the full utilization of family labor resource. The actual application of NPK fertilizer was determined to be excessive while application of organic matter was strongly suggested by the results of this study. The model has also confirmed that the capital fixed to PhP40,000.00 for one year was insufficient for cop production. With the capabilities of LGP model in ensuring a close distance from the desired objective, the farmer can set forth sound decisions regarding the allocation of land to efficiently utilize their available resources in farming.

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