| Abstract | The search for an optimal solution to the feed-mix problem is an integral part of the decision-making system in any feed manufacturing
concern. Since the cost of feed formulation accounts for more than 70% of the total manufacturing .cost, even small improvements in this area can have large financial effect on a narrow margin business like feed
manufacturing. In this study, a linear programming-based system model is first developed for aiding purchasing and operating decisions is one of the biggest agro-industrial firms in the Philippines. The study
limits itself to ten commercial mixed feeds and considers thirty-six candidate raw materials in feed formulation. The objective of the systems model is to minimize the total cost of feed production subject
to the nutritional constraints for each type of feed, and other
restrictions demanded by marketing and production men. The model produces two basic outputs, namely: (1) the detailed formulation for each type of feed on a monthly basis, and (2) a list of monthly raw material
requirement. These outputs, however, are dependent upon the accuracy of input data that are used, particularly the forecast of raw material prices. The study, therefore, provides an analysis of how sensitive are the required quantities of major feed ingredients to their predicted
prices. Since imported raw materials account for roughly 60% of the total raw material expenditure, the study focuses its post optimal analysis to five major imported feed ingredients, namely: yellow corn, fishmeal,
meat and bone meal, sorghum and soybean meal, In addition, this study explores the ramifications of changes in the stated problem after the
optimum feed formulas for the original problem have been determined. It analyzes the effects of changing the constraints dealing with the protein and metabolizable energy content of the feeds, and of deleting the restriction on feed bag volume. It also explores how the non availability of some raw materials would affect the raw material requirements and the
feed production cost. Finally, the study highlights areas where future studies can be undertaken to further reduce overall feed manufacturing costs. |