Logistics distribution scheduling model of supply chain based on genetic algorithm

This study aims to improve the efficiency of logistics distribution scheduling in the supply chain and reduce logistics costs. In the current research, the time and cost problems of logistics distribution always have some limitations to meet the needs of practical applications; therefore, this paper designed genetic algorithm-based method to solve the vehicle scheduling problem. The analysis of arithmetic examples was carried out. The analysis found that the method effectively reduced the cost of distribution and had higher computing speed, showing a high performance in solving the problem of logistics distribution scheduling. The method can further optimize the logistics distribution of the supply chain. This work provides a new approach for the study of logistics distribution scheduling model and is conducive to the better application of genetic algorithm in this field.

Automated summary

This study aims to improve the efficiency of logistics distribution scheduling in the supply chain and reduce costs, using a genetic algorithm-based method to solve vehicle scheduling problems. The method effectively reduces distribution costs, has higher computing speed, and provides a new approach for the study of logistics distribution scheduling models.