<![CDATA[Raising laying hens are considered a promising opportunity in Indonesia because the demand for eggs in the country continues to increase in line with the increasing human lifestyle and need for animal protein. Based on data from the ministry of agriculture in 2017 there is an increase in chicken egg consumption during the year 1987-2017 of 3.57% per year with an average consumption of 6.63 kg / kap / th in 2017. On the other hand, raising laying hens is costly especially when it comes to livestock feed, which can cost farmers 60% -70% of production costs. One way to reduce the cost of purchasing feed is by optimizing the feed composition, with purpose of achieving an optimal feed composition that also meets the nutritional needs, all obtained with as minimal cost as possible. The optimization method used in this research is Genetic Algorithm with permutation representation, single-point crossover, reciprocal exchange mutation, and elitism selection. This study used 50 feed data material of laying chicken and its nutritional content. From the results of the tests, the population parameters obtained with the highest fitness value in the population of 500 and 800 with the average fitness value of 2.573591, the optimal generation of 100 generations with an average fitness value of 2.479726 and a combination of probability of crossover 0.5 and the probability of mutation 0.3 with the average fitness value 2.58459. The final result is the composition of laying chicken feed that meets the nutritional needs with minimal cost.]]>
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