Abstract: The transportation industry,as one of the main contributors to carbon emissions,urgently needs effective carbon reduction reforms to help the country achieve thecarbon peaking and neutrality goals.Aiming at the current mainstream logistics center logistics model,a low-carbon oriented logistics optimization multi-objective model is established with the goals of minimizing carbon emissions per unit freight turnover,minimizing freight costs,and minimizing delivery time.The NSGA-II multi-objective genetic algorithm is improved based on the characteristics of this model and the characteristics of the scenario.An abstract data sample of an express company is used to test the effectiveness and progressiveness of the multi-objective optimization model and the improved NSGA-II algorithm.Experimental results show that from the perspectives of optimization scheduling and path planning,optimizing the entire distribution process through search and solution can effectively achieve the preset goal of cost control and carbon reduction,and provide theoretical basis for logistics enterprise distribution decision-making.The research results also indicate that carbon reduction and cost control are constraints in logistics,and different target preferences can have a significant impact on decision-making.

Key words: Low carbon oriented, Multi-objective optimization, Genetic algorithm, Scheduling optimization, Route planning