Optimization of Distribution Routes Using the Genetic Algorithm in the Traveling Salesman Problem
Abstract
Transportation plays a vital role in business operations, as it is essential for product distribution to maintain profitability. Optimizing distribution routes is crucial to reducing transportation costs, travel time, energy usage, and resource allocation while maximizing efficiency. Micro-entrepreneurs, particularly settled retailers, often face challenges in determining optimal travel routes, resulting in inefficiencies in product distribution. This issue is classified as a Traveling Salesman Problem (TSP), which involves finding the shortest possible route connecting several locations before returning to the starting point. To address this problem, this study applies a two-step approach: the greedy algorithm to provide an initial solution and the genetic algorithm for further optimization. The research employs both manual calculations and MATLAB 2018A software to solve the TSP. Results demonstrate that the optimized route reduces the travel distance by 1,260 meters compared to the initial solution, highlighting significant improvements in operational efficiency.
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References
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