Optimization of vehicle routing problems for cold chain logistics mixed fleet under low-carbon constraints

In the field of urban distribution, time-varying road network conditions are complex, customers' requirements for delivery time and freshness of goods are stringent, and the current situation of the coexistence of electric vehicles and fuel vehicles has brought new challenges and opportunities to logistics enterprises' distribution path optimization. Logistics enterprises need to optimize the distribution plan. This paper constructs a mixed fleet vehicle routing optimization model with multi factor considerations. Considering the key factors such as electric vehicle charging strategy, carbon emission cost and customer satisfaction, the minimum total distribution cost and the maximum customer satisfaction are the two objectives. In order to improve the efficiency and quality of the solution, this study designs and improves the NSGA-II algorithm, which integrates clustering, path rearrangement greedy strategy based on time window and cost optimization, and verifies the effectiveness of the improved NSGA-II algorithm through the numerical experiment of Solomon standard example, and makes a comparative analysis of the distribution schemes using mixed fleet and charging strategy, so as to help logistics enterprises determine the optimal charging strategy and distribution scheme.