Penentuan Komposisi Pakan Ternak untuk Memenuhi Kebutuhan Nutrisi Ayam Petelur dengan Biaya Minimum Menggunakan Particle Swarm Optimization (PSO) - Brigitta Ayu Kusuma Wardhany; Imam Cholissodin; Edy Santoso (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2017)
Feeding in accordance with nutritional needs of laying hens is the most important thing to be considered. This is because, the feed given will affect the amount and quality of the eggs produced. In addition, feed also affects the success of a chicken breeding business, where required a big amount of feed costs. So farmers must make an appropriate combination of the feed in order to obtain the minimum cost but with adequate nutrition. To obtain that feed combination, a research is conducted using Particle Swarm Optimization (PSO). PSO is one of the optimization methods that can solve the problems of feed combination to obtain the adequate nutrition of laying hens, so the farmer's income will be maximize. This research uses a real representation of code where each particles have long number with the data feed material used is 40. Each dimension in a particle represents the weight of the feed material. According to the test results, obtained the best parameters, such as swarm size = 350, number of iteration = 500, Ï‰max = 0.9 and Ï‰min = 0.4, c1i = 2.5 and c1f = 0.5 also c2i =0.5 and c2f = 2.5, then the best number of iteration according to the convergence test is 330. The final result is a combinational of best feed ingredients with nutritional met and minimum cost.