低碳定位——车辆路径问题

Location and routing problem with minimizing carbon

为降低物流配送过程中车辆的碳排放量,从低碳环保角度出发,建立以车辆碳排放量为函数目标的低碳定位—车辆路径问题数学模型,并采用量子进化算法结合局部搜索算法对模型进行求解。通过对比不同算法求解的结果,证明量子进化算法能有效的求解定位—路径问题模型。继而用量子进化算法求解低碳定位—车辆路径模型,在不同条件下计算车辆排放量、路径值与运行成本,探讨配送中心碳排放、配送路径对车辆碳排放的影响。采用数据比较的方法分析计算结果,证明了低碳定位—车辆路径数学模型能有效降低配送过程中的碳排放量,但总体成本将会增加。

To reduce the carbon emission of vehicles,the location-routing problem model by taking minimum carbon emission as objective was built,which was solved by Quantum Evolutionary Algorithm（QEA）with local search method.By comparing with the solution result of different algorithms,the effectiveness of QEA for solving locationrouting problem model was proved.The low carbon location-routing problem was solved with QEA,and the carbon emission based on a set of benchmarks data were calculated and their influence factor were analyzed.Through analyzing the computational result,the carbon emission could be reduced effectively with proposed model,but the general cost would be increased.