“双碳”背景下联合配送冷链物流模型及其求解算法

Cold chain logistics model based on joint distribution and its optimization algorithm under the background of double carbon

首先,基于“双碳”战略目标的提出以及物流企业低碳转型的发展趋势,以多中心冷链物流绿色车辆路径问题为研究对象,以碳排放成本、配送成本和时间窗惩罚成本之和最小化为优化目标,建立考虑联合配送和碳交易机制的冷链物流模型;然后,针对遗传算法局部搜索能力差、收敛速度慢等缺点,设计一种具有变邻域搜索操作和动态灾变机制的多种群遗传算法,以标准算例集验证该算法在寻优能力、稳定性、收敛速度等方面的优势;最后,通过实验验证所提出模型的有效性,并从联合配送、决策目标、碳交易机制等多角度进行分析,为冷链物流企业和政府提供管理启示.

Under the background of the“double carbon”objective and the low carbon transformation of logistics enterprises,a cold chain logistics model based on joint distribution and carbon trading mechanism is constructed.The model takes the multi-depot green vehicle routing problem in cold chain logistics as the research object,and minimizes carbon emission cost,distribution cost and time window penalty cost as the optimization objective.Then,a multiple population genetic algorithm with variable neighborhood search and dynamic catastrophe mechanism is designed to address the disadvantages of poor local search ability and slow convergence of genetic algorithms.And the advantages of the algorithm in terms of optimization ability,stability and convergence speed are confirmed by the standard instances.Finally,an example is analyzed from various perspectives such as joint distribution,objectives and carbon trading mechanism to verify the validity of the model and provide management insights for cold chain logistics enterprises and governments.