关键词: 低碳车辆路径问题, 碳排放, 改进蚁群算法, 混沌扰动机制

Abstract: Global climate deterioration endangers human living environment, and the large amount of greenhouse gases produced in the process of logistics transportation which is flourishing nowadays is one of the main causes of this disaster. Carbon emission control of vehicles in logistics transportation industry can help promote the development of green logistics transportation industry, so that great contributions to environment protection can be made. The key to solve this problem is to achieve the shortest running path(the lowest running cost) of the traditional vehicle routing problem, and to ensure that the carbon emission of vehicles in the running process are effectively reduced at the same time.Aim at offering some theoretical suggestions to the problem discussed above, the vehicle routing problem(VRP) with carbon emission constrain is studied in this paper. Firstly, a multi-objective VRP optimization model is established, which contains the objectives of minimizing vehicle mileage and carbon emission. When calculating the vehicle carbon emission, influence factors such as vehicle type, load, speed, travel distance and even road condition are all taken into consideration comprehensively. This can be a good supplement to the research and design of similar literature. Then an improved ant colony system algorithm is proposed to solve the model. Chaotic disturbance mechanism is introduced to update the ant pheromones on the path, which reduces the probability of falling into local optimal solution while the algorithm is running, and effectively improves the adaptability of the algorithm. At the same time, the heuristic factor, state transition probability and pheromone updating are optimized to improve the search efficiency of optimal path.Finally, the numerical simulation results show that this algorithm outperforms genetic algorithm and tabu search algorithm which are commonly used in the same kind of research, and it has strong global optimization ability. Under the guarantee of sensitivity and effectiveness, the improved ant colony algorithm designed in this studyis another feasible heuristic algorithmfor low-carbon vehicle routing problem, and its performance is comparatively good.

Key words: low-carbon vehicle routing problem, carbon emission, modified ant colony algorithm, chaos disturbance mechanism