College of Mechanical Engineering, Chongqing University, Chongqing 400044, China.
School of Economics and Business Administration, Chongqing University, Chongqing 400044, China.
Int J Environ Res Public Health. 2018 Sep 17;15(9):2025. doi: 10.3390/ijerph15092025.
In order to cut the costs of third-party logistics companies and respond to the Chinese government's low-carbon economy plans, this paper studies the more practical and complex open vehicle routing problem, which considers low-carbon trading policies. A low-carbon multi-depot open vehicle routing problem with time windows (MDOVRPTW) model is constructed with minimum total costs, which include the driver's salary, penalty costs, fuel costs and carbon emissions trading costs. Then, a two-phase algorithm is proposed to handle the model. In the first phase, the initial local solution is obtained with particle swarm optimization (PSO); in the second phase, we can obtain a global optimal solution through a further tabu search (TS). Experiments proved that the proposed algorithm is more suitable for small-scale cases. Furthermore, a series of experiments with different values of carbon prices and carbon quotas are conducted. The results of the study indicate that, as carbon trading prices and carbon quotas change, total costs, carbon emission trading costs and carbon emissions are affected accordingly. Based on these academic results, this paper presents some effective proposals for the government's carbon trading policy-making and also for logistics companies to have better route planning under carbon emission constraints.
为了降低第三方物流企业的成本,并响应中国政府的低碳经济计划,本文研究了更实际和复杂的开放车辆路径问题,该问题考虑了低碳交易政策。构建了具有时间窗的低碳多仓库开放式车辆路径问题(MDOVRPTW)模型,以最小总成本为目标,总成本包括驾驶员工资、罚款成本、燃料成本和碳排放交易成本。然后,提出了一种两阶段算法来处理该模型。在第一阶段,使用粒子群优化(PSO)获得初始局部解;在第二阶段,通过进一步的禁忌搜索(TS)获得全局最优解。实验证明,所提出的算法更适用于小规模情况。此外,还进行了一系列不同碳价和碳配额的实验。研究结果表明,随着碳交易价格和碳配额的变化,总成本、碳排放交易成本和碳排放也会相应受到影响。基于这些学术成果,本文为政府的碳交易政策制定以及物流企业在碳排放约束下更好地进行路径规划提供了一些有效的建议。