Optimasi Penjadwalan Transportasi untuk Efisiensi Distribusi Beras di Sumatera Utara dengan Algoritma Genetika (Studi Kasus: Perum Bulog Medan)

Abstract

The intercity rice distribution system in North Sumatra, managed by Perum Bulog Medan, continues to face significant challenges in the form of high transportation costs and suboptimal delivery scheduling. This study aims to develop an optimization model for transportation scheduling to minimize distribution costs while still considering operational constraints such as vehicle capacity, travel time, and fleet availability. The proposed method applies a Genetic Algorithm (GA), using actual distribution data from Gatot Subroto and Mustafa. The model was implemented using Python programming language. Simulation results show that GA successfully reduced the total distribution cost from IDR 5.399.566.000 to IDR 3.359.393.000, achieving cost savings of approximately 38%. The optimized solution complies with all predefined operational constraints. A paired t- test analysis confirms that the proposed optimization model has a statistically significant impact on cost efficiency. Therefore, the use of Genetic Algorithm is proven to be effective in improving transportation scheduling and enhancing the efficiency of rice distribution logistics in North Sumatra.