DEVELOPMENT OF HYBRID GENETIC ALGORITHM-BASED MODEL FOR POULTRYFEED FORMULATION

Abstract

The poultry industry has a significant importance on national economy. It is a popular industry for the small holders with tremendous contribution to gross domestic product (GDP) and employment creation. Poultry feed cost represents a significant cost of poultry production. Consequently, efficient feed formulation practice is required for a sustainable poultry production. Many poultry farmers, however, employ inefficient methods like rule of thumb and intuition to handle feed formulation problem. The aim of this research is to develop an optimization feed formulation model which can be used to harness the potentials of locally available feed ingredients to produce a balanced poultry feed. To achieve this aim, genetic-tabu search algorithm model was developed for layers mash feed formulation. Thirteen (13) decision variables and eight (8) constraints were identified and used in the research. Secondary data were collected from the recommended nutrient requirements schedule from Ondo State Ministry of Agriculture and Freedom Feed Mill (a local feed miller) in Akure, Ondo State, Nigeria.Based on this data, the optimal solution of the genetic-tabu search algorithm model developed for the layers mash compared to the existing methods of feed formulation produced a feed at a reduced cost that contains the right proportion of nutrients.