摘要
针对医药冷链行业高成本、高能耗、高碳排放等问题,文章在传统医药冷链配送模型的基础上,考虑时间窗、载重量、碳排放等约束条件,将碳排放以碳税机制货币化,构建了以碳排放成本、固定成本、运输成本、医药货损成本、制冷成本为总配送成本的数学模型。同时根据模型特点和传统遗传算法较容易进入局部最优的情况,进一步优化了交叉、变异算子,同时导入模拟退火算法,并提出了一种遗传算法和模拟退火算法相结合的混合遗传算法,最后通过对H制药企业进行算例求解,将传统遗传算法和改进遗传算法进行了比较,结果表明优化后的遗传算法相较于传统的遗传算法找到的配送路径更优,在降低总配送成本和碳排放成本上具有显著效果,对于求解医药配送冷链路径优化问题具有较好的适用性。
Pharmaceutical cold chain industry has been suffering from high cost,high energy consumption,high carbon emis⁃sions and other problems.Based on the traditional pharmaceutical cold chain distribution model,the article considers the con⁃straints such as time window,load capacity,carbon emissions,monetizes the carbon emissions with the carbon tax mechanism,and constructs a mathematical model with the carbon emission cost,fixed cost,transportation cost,pharmaceutical cargo dam⁃age cost,refrigeration cost as the total distribution cost.At the same time,according to the characteristics of the model and the situation that the traditional genetic algorithm is easier to enter the local optimum,the paper further optimizes the cross⁃over and mutation operators,and meanwhile,imports the simulated annealing algorithm,and puts forward a hybrid genetic algo⁃rithm combining the genetic algorithm and simulated annealing algorithm.Finally,through solving the case of the H pharma⁃ceutical enterprise,the article compares the traditional genetic algorithm and the improved genetic algorithm,and the result shows that the optimized genetic algorithm finds a better distribution path compared with the traditional genetic algorithm,and it has a significant effect on reducing the total distribution cost and carbon emission cost,which is suitable for solving the op⁃timization problem of cold chain path for pharmaceutical distribution.
作者
李晓睿
邢春玉
LI Xiaorui;XING Chunyu(School of Information Management,Beijing University of Information Technology,Beijing 100080,China)
出处
《物流科技》
2025年第24期165-172,共8页
Logistics Sci Tech
基金
北京市教育委员会科学研究计划项目资助“京津冀一体化市场环境对高科技企业创新发展影响研究”(SM202111232006)。
关键词
路径优化
医药冷链
低碳物流
混合遗传算法
path optimization
medical cold chain
low carbon logistics
hybrid genetic algoritm
