Abstract
Efficient truck route optimization is crucial for enhancing operational efficiency and reducing costs in urban logistics and freight distribution. This study addresses the Vehicle Routing Problem with Time Windows (VRPTW), focusing on task allocation and path planning while considering key constraints such as delivery time windows and vehicle capacity. To tackle these challenges, we propose an innovative approach: the Improved Elite Retention Genetic Algorithm (IE-GA-VRPTW). By integrating dynamic crowding mechanisms and elite retention strategies, this method enhances solution quality and accelerates convergence speed, thereby minimizing total travel distance, fuel consumption, and time penalty costs. Comprehensive case studies demonstrate that IE-GA-VRPTW significantly outperforms traditional optimization techniques, achieving a substantial reduction in fuel consumption while ensuring compliance with delivery time windows. This approach provides valuable insights for optimizing freight distribution, contributing to the development of more sustainable and efficient urban logistics systems.