摘要
随着经济的发展,人民生活水平不断提高,人们对新鲜食品的需求与日俱增,极大地促进了冷链物流行业的发展,但也给生态环境带来许多负面的影响,与当今倡导的低碳经济发展相悖。基于此背景,文章将碳排放转化为成本融入到生鲜农产品冷链物流配送路径优化问题中,以碳排放成本、冷藏车辆固定费用、时间窗惩罚成本、生鲜损耗成本、燃油消耗费用的综合总成本最小为目标,构建带有时间窗限制的生鲜农产品冷链物流配送路径的数学模型。在模型求解中分别采用基本的蚁群算法与改进的邻域搜索蚁群算法,利用Matlab对模型进行编码例算。通过比较结果得知,利用改进的邻域搜索蚁群算法搜寻出的最优路径可以缩短配送距离,明显降低碳排放量,实现总成本最低。文章可为现实中经营的生鲜农产品配送企业提供参考意见,具有一定实际意义。
With the development of economy and the improvement of people's living standard,people's demand for fresh food was increasing day by day,which didn t only greatly promote the development of cold chain logistics industry,but also brought many negative impacts to ecological environment,which was contrary to the development of low carbon economy advocated today.Based on this background,in this paper we integrated carbon emission into cost fo the fresh agricultural products cold chain logistics distribution path optimization problem,and constructed a mathematical model of fresh agricultural products cold chain logistics distribution path with time window limitation with the goal of minimizing the total cost of carbon emission,fixed cost of refrigerated vehicles,time window penalty cost,fresh loss cost and fuel consumption cost.The basic ant colony algorithm and the improved neighborhood search ant colony algorithm were used in the model solution,and the model was coded with Matlab for example calculations.By comparing the results,we knew that the optimal route searched by the improved neighborhood search ant colony algorithm could shorten the distribution distance,significantly reduce carbon emissions,and achieve the lowest total cost.This mathematical model could provide a reference for fresh produce distribution enterprises operating in reality and had some practical significance.
作者
程元栋
韩佰庆
CHENG Yuandong;HAN Baiqing(Department of Economics and Management,Anhui University of Science and Technology,Huainan,Anhui 232000,China)
出处
《九江学院学报（自然科学版）》
CAS
2023年第1期17-25,30,共10页
Journal of Jiujiang University：Natural Science Edition
基金
国家自然科学基金项目(编号71473001)
安徽省哲学社会科学规划项目(编号AHSKY2017D35)
安徽省教育厅人文社科重点项目(编号SK2020A0212)的研究成果之一
关键词
碳排放
生鲜农产品
冷链物流
路径优化
邻域搜索
蚁群算法
carbon emissions
fresh produce
cold chain logistics
path optimization
neighborhood search
ant colony algorithm
