考虑低碳因素的无水港扩展以及运量分配方案

Expansion of dry port and traffic volume distribution scheme considering low-carbon factors

针对现有的无水港已经难以满足日益增长的货运需求的情况,依据无水港枢纽规划扩展需求,考虑在货物运输、装卸以及更换交通运输方式时的碳排放,创新地将碳税添加进成本之中,构建以运输时间最少和运输网络成本最小为目标,以低碳为要素的运输枢纽扩展和运量分配的双目标模型,以解决运输网络扩展的问题。以宁波港及其涉及的运输网络为例,使用粒子群优化算法及量子粒子群优化算法对模型进行求解,并对2种算法的结果进行对比,择优选择量子粒子群优化算法求解出无水港扩展方案和新的运量分配方案。结果表明:与原运输网络相比,扩展内陆城市为无水港枢纽能增加网络的运量处理能力,降低货物运输时间,提高了货运网络的运输能力。

In view of the fact that the existing dry port has been difficult to meet the growing freight demand, according to the expansion demand of dry port hub planning, considering the carbon emission during cargo transportation, loading and unloading and changing transportation modes, this paper innovatively adds carbon tax to the cost, and constructs a dual objective model of transportation hub expansion and traffic volume allocation with the minimum transportation time and transportation network cost as the goal and low carbon as the element, To solve the problem of transportation network expansion. Taking Ningbo port and its transportation network as an example, this paper uses particle swarm optimization algorithm and quantum particle swarm optimization algorithm to solve the model, compares the results of the two algorithms, and selects the quantum particle swarm optimization algorithm to solve the dry port expansion scheme and the new traffic volume allocation scheme. The results show that compared with the original transportation network, expanding the inland city into a dry port hub can increase the transportation capacity of the network, reduce the cargo transportation time, and effectively improve the transportation capacity of the freight network.