Pu Xujin, Lu Xulong, Han Guanghua
School of Business, Jiangnan University, Wuxi, 214122, China.
School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai, 200030, China.
Environ Sci Pollut Res Int. 2022 Aug;29(36):54940-54955. doi: 10.1007/s11356-022-19370-0. Epub 2022 Mar 21.
In a multi-depot vehicle routing problem (MDVRP) of same-city delivery, driving distance and actual loading can greatly influence the amount of carbon emissions generated. This paper considers fuel and carbon emission costs as part of total costs, proposes a MDVRP with minimized logistics costs and driven distance, and then establishes a mixed integer programming model. An improved chemical reaction optimization algorithm is also designed by considering this problem's characteristics (i.e., a greedy search strategy is presented to generate an initial population), and two coding approaches (i.e., two-part coding and matrix coding) are applied prior to designing four chemical reaction operators. The simulation experiment is carried out using a set of a random instances and the experimental results demonstrate that one can reduce carbon emissions by driving extra lesser distances, providing a methodological guide for MDVRPs with logistics costs and carbon emissions.
在同城配送的多配送中心车辆路径问题（MDVRP）中，行驶距离和实际装载量会极大地影响碳排放量。本文将燃料和碳排放成本视为总成本的一部分，提出了一种使物流成本和行驶距离最小化的MDVRP，进而建立了混合整数规划模型。通过考虑该问题的特点（即提出一种贪婪搜索策略来生成初始种群）设计了一种改进的化学反应优化算法，并且在设计四个化学反应算子之前应用了两种编码方法（即两部分编码和矩阵编码）。使用一组随机实例进行了仿真实验，实验结果表明，可以通过额外行驶更短的距离来减少碳排放，为具有物流成本和碳排放的MDVRP提供了方法指导。
