基于改进遗传算法的卷烟物流配送线路优化模型构建

On the Optimization Model Construction of Cigarette Logistics Distribution Route Based on Improved Genetic Algorithm

为推进烟草行业的高质量发展,围绕“引领撬动,加快数字化转型”总目标,文章以人工智能深度学习算法与卷烟物流配送业务的融合创新为研究方向,积极探索物联网、云计算等IT新技术与卷烟物流配送环节的深度融合,提出并构建了一种基于改进遗传算法的卷烟物流配送线路优化模型,并结合DMAIC管理模式推动了卷烟物流配送线路从固定模式向动态调整方式转变,从而有效地缩短送货里程、减少送货车次和配送成本,提高日均送货户数和人均配送效率。

In order to promote the high-quality development of the tobacco industry,centering on the overall goal of“leading and accelerating the digital transformation”,the paper takes the integration and innovation of the deep learning algorithm of artif icial intelligence and cigarette logistics distribution business as the research direction,and actively explores the deep integration of the Internet of Things,cloud computing and other new IT technologies and cigarette logistics distribution links.A cigarette logistics distribution routing optimization model based on improved genetic algorithm is proposed and constructed,and the DMAIC management mode is combined to promote the transformation of cigarette logistics distribution routing from fixed mode to dynamic adjustment mode,so as to effectively shorten the delivery mileage,reduce the number of delivery vehicles and distribution costs,and improve the average number of daily delivery households and per capita distribution efficiency.