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|Title:||Linear Programming of Large and Small Container Nurseries|
|Author(s):||Sabota, Catherine Marie|
|Department / Program:||Horticulture|
|Degree Granting Institution:||University of Illinois at Urbana-Champaign|
|Abstract:||With the evolution of the computer, linear programming holds possibilities for nursery reorganization. Exploration of these possibilities is the primary aim of this study.
Ten container plant nurseries were chosen for this study to determine possible production systems and their inputs. Large (average 27 ha) and small (average 5 ha) container nurseries were separated and a model was developed for each. The activities in the model were genera x container size or product type. The small nursery model had 44 product type alternatives and the large nursery model had 87. The resources included in the constraints were equipment, materials and labor utilized to produce each product type.
The initial analysis of the small nursery placed upper bounds of 1,000 (S1) or 5,000 (S2) plants/product type. The optimal crop mix for the S1 model included 1,000 plants of 3 gallon Viburnum, Cotoneaster, Rhus, Syringa and Juniperus and 658 3 gallon Spiraea. The value of the objective function (gross marginal revenue) for the S1 crop mix was $33,848. The optimal crop mix for the S2 model was 5,000 3 gallon Viburnum and 1,085 3 gallon Cotoneaster which resulted in a marginal gross revenue of $52,844. The shadow prices of the activities that reached their upper bounds were greater than the cost to produce them and the objective function could be increased with an increase in the upper bounds.
Sensitivity analysis of the various models revealed the upper and lower ranges that would vary the optimal crop mix. As well, the cost ranges of materials, labor and equipment indicated the maximum cost level before the optimal crop mix would change. Sensitivity analysis of the right hand side values for media, polyhouse area, and labor costs indicated the maximum and minimum values that would change the optimal crop mix and the level of change that would occur in the objective function.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1983.
|Date Available in IDEALS:||2014-12-16|