OPTIMIZATION OF FROZEN FOOD DISTRIBUTION USING GENETIC ALGORITHMS - Widdia Lesmawati; Asyrofa Rahmi; Wayan Firdaus Mahmudy (Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya, 2016)
Nowadays, 30% of Indonesian consume frozen foods because it is more practical and efficient. The increase of demand requires a good distribution system. The distribution problem can be solved using genetic algorithms. Crossover method used in this study is one-cut point crossover, the mutation method used is reciprocal exchange mutation and the selection method used is elitism selection. The data used in this study is 15 of customers, 11 of product types, 5 vehicles and distance data between regions. From the tests, we found that optimal results are achieved using the population size of 1950, 700 generations, a combination of crossover rate (cr) = 0.5 and mutation rate (mr) = 0.6. The final result is a combination of the customer and vehicle order that distribute all products to all customers with the minimum total distance and cost.