Optimasi Komposisi Makanan Untuk Ibu Hamil Menggunakan Hybrid Algoritme Genetika dan Simulated Annealing - Fatthul Iman; Dian Eka Ratnawati; Titis Sari Kusuma (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
The imbalance between the nutritional intake of pregnant women to meet the needs and energy expenditure must always be monitored, because the imbalance itself can result in Chronic Energy Deficiency both in mother and fetus in the womb. Therefore it needs an appropriate food composition to meet the nutrients and energy for pregnant women, so it can help them to determine their own food. The problem of food composition for pregnant women can be solved by hybrid genetic algorithm and Simulated Annealing. The purpose of combining this method is to produce a better solution than using a genetic algorithm alone. This problem solving process have used crossover method is one-cut point, mutation using reciprocal exchange method, selection using elitsm, and Simulated Annealing. Based on the results of the test of the parameters used in the optimization system of food composition that using genetic algorithm hybrid and Simulated Annealing, was obtained the best parameter values ​​are: population number = 2900, Cr = 0.4, Mr = 0.6, T0 = 1, alpha = 0.7 and the number of generations = 220. So the results of the system is in the form of food composition recommendation using hybrid genetic algorithm and Simulated Annealing that can meet the tolerance limit set by the nutritionists at ± 10%.