Optimasi Komposisi Pakan Untuk Memenuhi Kebutuhan Nutrisi Ayam Petelur dengan Biaya Minimum Menggunakan Improved Particle Swarm Optimization (IPSO) - Nur Firra Hasjidla; Imam Cholissodin; Agus Wahyu Widodo (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
In a business of laying hens farm, the feed costs constitute as much as 60-70 percent of the total cost of livestock production. Breeders can compose rations for their laying hens independently to save the feed costs. However, in the making of rations, breeders must examine the nutrient content and price of each feed ingredient that will be combined first. Breeders also have to evaluate manually whether the ration formula that will be given can fulfill the nutritional needs of laying hens. Therefore, to improve the efficiency of feeding in accordance with the nutritional needs of laying hens and with minimum cost, this study designed a system to determine the optimal layer feed composition using Improved Particle Swarm Optimization (IPSO) algorithm, an optimization technique which is a development of the PSO algorithm. Particles move in search space to find solutions. From the test results obtained optimal values for each IPSO's parameter, population size = 250, maximum iteration = 350, and the interval of feed ingredient weight = 1-70%. IPSO algorithm is able to give solution of feed composition with cost 50.41% cheaper than one of the data from laying hens breeder.