Enhancing logistics efficiency: A case study of genetic algorithm-based route optimization in distribution problem

Abstract

The optimization of route planning is a critical consideration frequently happened in the logistics of product distribution. This study addresses distribution issues, such as long trip distances, which result in high distribution costs. The objective of this research is to increase distribution routes' effectiveness, which will enable it to reach the minimize distance and lower the cost of product distribution. The Travelling Salesman Problem (TSP) can be resolved by using the Genetic Algorithm (GA) technique to optimize the path. Variations in crossover, mutation, and population were made when experimenting with GA. The results of the study indicate that the overall distance travelled decreased from 55.5 km to 30.45 km and that the cost of distributing the product was reduced from Rp 94,350.00 to Rp 51,765.00. There is a about 45% improvement. There is about 45% improvement. This optimisation technique has a favourable effect on the overall financial performance and competitiveness of businesses involved in comparable distribution operations, as well as improving operational efficiency and offering the possibility of cost savings.

Keywords

• travelling salesman problem
• genetic algorithm
• distribution