| Summary: | The aim of this research is to determine the optimal route using a genetic algorithm and to compare the routes before and after optimization. The method used is the Genetic Algorithm, which consists of representation and initialization stages using permutation encode representation of the sequence of travel routes. The fitness function evaluation is the minimization of total fuel cost, selection is done using roulette wheel selection, crossover is done using PMX, and mutation is done using swap mutation. The testing of parameter combinations is carried out on population size, Cr and Mr values, and the number of generations. The parameter testing based on the highest average fitness is conducted 10 times for each parameter combination. Testing of population size and generation size was carried out in the range of 100-1000, obtained the best population size of 600 and the best generation size of 900. The combination testing of Cr and Mr is conducted for combinations of 1 and more than 1, and the values obtained are Cr: 0.6 and Mr: 0.5. This combination of parameters results in a fitness of 0.00960 with a total distance traveled of 307.61 and a total transportation cost of Rp 104,082 for fuel. Initially, the total distance traveled was 278.57 km with a fuel distribution cost of Rp 161,258. Therefore, the results of this research are able to save 35.46% of fuel transportation costs.
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