摘要
为解决城市生鲜产品配送距离过长、配送成本和碳排放量高的问题,提出一种以配送成本最小化为目标的冷链物流路径优化模型。该模型在考虑车辆固定成本、运输成本、货损成本、制冷成本和惩罚成本的基础上引入碳排放成本,并采用改进的大邻域搜索遗传算法进行路径求解。结果显示:改进算法较传统遗传算法迭代次数减少约50%,总成本降低940.321元,碳排放量减少98.600 kg;考虑碳排放的模型较不考虑的方案总成本减少481.804元,碳排放量减少56.485 kg。此结果证明了该模型和算法的可行性。
To address the issues of excessive delivery distances,high distribution costs,and elevated carbon emissions in urban fresh product logistics,a cold chain logistics route optimization model aimed at minimizing distribution costs was proposed.This model incorporates carbon emission costs while considering fixed vehicle costs,transportation costs,goods spoilage costs,refrigeration costs,and penalty costs.An improved large neighborhood search genetic algorithm was employed to solve the routing problem.The results indicate that compared with the traditional genetic algorithm,the improved algorithm reduces the number of iterations by approximately 50%,the total cost by 940.321 yuan,and the carbon emissions by 98.600 kg.Additionally,in contrast to the scheme without considering carbon emissions,the model incorporating carbon emissions achieves a reduction of 481.804 yuan in total cost and 56.485 kg in carbon emissions.These results demonstrate the feasibility of the proposed model and algorithm.
作者
涂斌斌
李美兰
王飞
TU Binbin;LI Meilan;WANG Fei(School of Intelligent Science and Information Engineering,Shenyang University,Shenyang 110044,China)
出处
《沈阳大学学报(自然科学版)》
2025年第6期496-504,F0003,共10页
Journal of Shenyang University(Natural Science)
基金
国家自然科学基金资助项目(71672117)
辽宁省科技计划项目(2023JH2/101300205)。
关键词
双碳
生鲜产品
冷链物流
路径优化
大邻域搜索
遗传算法
carbon peaking and carbon neutrality
fresh products
cold chain logistics
path optimization
large neighborhood search
genetic algorithm
