Selection of Optimal Transportation Routes in the Distribution of Temanggung Original Robusta Coffee using Genetic Algorithms

Abstract

The selection of optimal transportation routes in the distribution of agro-industrial commodities consists of the need to visit locations that are the safest and optimal by considering the risk of commodity damage. In practice, the amount of time available is limited, complex, and uncertain, so metaheuristic algorithms are used. This study aims to help decision-makers choose the optimal transportation route in the original Temanggung robusta coffee distribution using Genetic Algorithms (GA). We used five interrelated research variables: location point, modes of transportation, path traversed, vehicle capacity, and distribution cost. We discussed the construction of the population, chromosome representation, fitness function, natural selection, crossover, and mutation. The results showed that the minimum distance traveled was 264.8 Km, the chromosomes having that distance were Z1" – Z2" – Z5" – Z3" – Z4" – Z6" – Z8" – Z7", and all chromosomes have the same route, namely Node1 – Node2 – Node5 – Node3 – Node4 – Node6 – Node8 – Node7. The results of GA transportation optimization can find the minimum solution. It shows that GA can be used to choose the optimal transportation route in the distribution of the original robusta coffee of Temanggung. For further research, researchers can add resistance variables at each node.