摘要
物流不仅是能源消耗大户,同时也是CO2排放的重要来源。在分析配送车辆燃油消耗和CO2排放因素的多种车辆类型车辆路径问题特点的基础上,构建其相应的优化模型,并给出基于遗传算法的启发式求解算法。最后,针对该模型和求解算法进行数值算例仿真,研究结果显示:路径最短的路线不一定是能耗最小的路线;与传统基于路径最短的车辆路径对比,基于CO2排放的车辆路径总行驶里程较长,但其综合成本较低;遗传算法是解决绿色车辆路径问题的一个有效的求解算法。
Logistics is not only the major part of energy consumption, but also an important source of CO2 emissions. When considering the characteristics of energy consumption and CO2 emission factors in vehicle routing problem with multiple vehicles, the corresponding optimization model was constructed, and a heuristic algorithm was given based on genetic algorithm. Finally, numerical simulation was performed for the model and solution algorithm. The results show that the shortest route is not always the least energy consumption route. When compared with the traditional shortest path vehicle routing, vehicle routing based on CO2 emissions has a longer path length, but with a lower comprehensive cost. Genetic algorithm is an effective algorithm to solve the green vehicle routing problem.
出处
《铁道科学与工程学报》
CAS
CSCD
北大核心
2015年第2期424-429,共6页
Journal of Railway Science and Engineering
基金
国家社科基金资助项目(11CGL032)
国家自然科学基金资助项目(71271220)
关键词
物流能耗
CO2排放
车辆路径
优化模型
遗传算法
logistics energy consumption
CO2 emission
vehicle routing
optimization model
genetic algorithm
