Research On Vehicle Routing Optimization Modeling With Considering Carbon Emission Factor

With the deepening of global economic integration, China’s economy has a rapid development, at the same time it is also showing a growing trend in the energy consumption. Particularly, China’s carbon emissions is from 14.5 tons in 1980, a sharp rise to 100 tons in 2013, ranking first in the world, and occupy 29% of the total global emissions. Research shows that logistics distribution has become one of the most important sources of global carbon emissions, which accounts for 14% of the total share of greenhouse gas emissions. Compared with USA 12% and European Union 11%, China’s greenhouse gas emissions in logistics industry take up as much as 19% of the total greenhouse gas emissions. So, in order to reduce carbon emissions in China’s logistics industry, it is a vital importance to research the vehicle routing problem considering carbon emission factors. This article emphasized on vehicle routing model considering carbon emissions factors and optimization method, the specific research content and innovation are as follows:In the first place, considering the need of computing the amount of freight vehicles’ carbon emissions, we compare and analyze the carbon emissions calculation model. Then, for the interest of simplicity and operability in calculation, we simplify the calculation model. As logistics enterprises may be involved in carbon trading along with the potentials of buying and selling of carbon emissions as well as carbon punishment, this paper researches carbon trading mechanism and model with carbon punishment that is suitable for the logistics distribution enterprises, and also analyze the impact of fluctuation in carbon trading mechanism on the logistics distribution.Secondly, for solving the vehicle routing problem, the paper establishes multi-objective integer programming model with carbon emissions and time window. Considering the complexity of solving the model, we design a new hybrid genetic algorithm combining with clustering analysis method, scanning algorithm and both sides of successive correction algorithm. Cluster analysis technology can classify the customers according to their discrete situation, and further reduce invalid search. Then, the use of scanning algorithm can quickly make sort of similar customers to avoid individuals of poor fitness; and finally both sides of successive correction algorithm can re-optimize the optimized sub-path to improve the performance of the algorithm. To verify the performance of the algorithm, standard examples are used to test the algorithm’s validity and reliability.Finally, the paper verify the vehicle routing model considering carbon emission’s factors and the designed hybrid genetic algorithm with logistics distribution case in Chongqing Tianyou Dairy Co.,LTD. At the same time, the paper discusses the impact on logistics distribution with case of single vehicle type, hybrid vehicle types, the amount of carbon trading under different proportions, different carbon trading punishment prices. In addition, compared to heuristic algorithm we try to verify the practicality and stability of the designed hybrid genetic algorithm.The main contributions of this paper are as follows. First, we make a summarization of distribution vehicle’s carbon emissions calculation models, and choose the suitable one for the article, we also establish a carbon trading mechanisms and discuss the impact on logistics distribution. Second, the paper establish a multi-objective vehicle path integer programming model considering carbon emissions and the time window for the research problem, and design a hybrid genetic algorithm to address the complexity in solving the model, and use numerical examples to test the model and algorithm. Third, we use cases to further verify the vehicle routing model considering carbon emissions and solution algorithm.