Optimization method for logistics distribution path based on soft time window and HC-GA

A logistics distribution path optimization method based on soft time windows and hill climbing genetic algorithms is proposed to reduce costs and achieve low-carbon transport. Experimental results show the improved algorithm converges after 20 iterations with a fitness of 4.93×10⁵, lower than others. It averages 20 iterations and 3.1 seconds, indicating high efficiency. In example C105, the path length is 843.70 km, below others. In a practical test with a chain supermarket, the delivery path length is 367.5 km, reduced by at least 14.9%. Total cost is 1873.6 yuan and carbon emissions are 109.1 kg, both lower. Vehicle load capacity exceeds 80%, improving utilization. Under multiple distribution centers, delivery time is shorter and demand coverage averages 96.5%, better than others. The algorithm effectively reduces costs, emissions, and enhances efficiency, with high application value.