Putri Farah Salsabela, Rudi Nurdiansyah
Optimization serves as a key process in finding the most effective solutions for various challenges, including those in e-commerce logistics. This study evaluates the performance of two metaheuristic algorithms, Differential Evolution (DE) and Harmony Search (HS) in optimizing last-mile delivery routes, which are modeled using the Traveling Salesman Problem (TSP). The increasing growth of e-commerce in Indonesia drives the need for an efficient logistics network, particularly in selecting the most optimal delivery routes. Real delivery data supports the assessment of each algorithm's ability to reduce operational costs and enhance customer satisfaction. The results indicate that Differential Evolution consistently generates shorter route distances and achieves faster convergence compared to Harmony Search, making it the more effective algorithm in this context. This approach contributes to the development of a more optimal and applicable delivery route planning method in logistics operations. © 2025 IEEE.
Universitas Negeri Malang, Department of Mechanical and Industrial Engineering, Malang, Indonesia
