基于混流生产的农机制造物料配送期量优化研究  

Research on Optimization of Distribution Period of Agricultural Machinery Manufacturing Materials Based on Mixed-flow Production

作　　者：王保森 吕锋[1] 张雷雷 WANG Baosen;LV Feng;ZHANG Leilei(School of Mechatronics Engineering,Henan University of Science and Technology,Luoyang 471003,China;China Yituo Group Co.,Ltd,Luoyang 471004,China)

机构地区：[1]河南科技大学机电工程学院,河南洛阳471003 [2]中国一拖股份有限公司,河南洛阳471004

出　　处：《物流科技》2024年第13期1-5,共5页Logistics Sci-Tech

基　　金：国家重点研发计划项目(2020YFB1713500)。

摘　　要：针对传统物料配送方式难以满足农机制造混流生产的问题,提出多品种小批量的物料配送期量优化方法,解决农机制造商仓储中心向线边配送物料过程中存在的配送总成本高、线边库存大、配送不及时等问题。以配送总成本、AGV配送小车装载空置率为优化目标,构建了多目标、多频次、小批量物料配送期量优化模型。根据模型决策变量的特征,设计了改进种群初始化生成方法和改进收敛因子的多目标灰狼优化算法,提高了算法寻优和收敛能力。实例验证了模型和算法的可行性和有效性。研究结果表明:较优化前,总配送成本减少21.3%,平均配送间隔期缩短23.4%,减少了库存积压和浪费,实现了多品种物料配送期量优化,有效降低了配送总成本。In response to the problem of mixed agricultural machinery manufacturing mixed production methods,it is difficult to meet the problem of agricultural machinery manufacturing mixed production.Large,not timely delivery and other issues.Based on the total delivery cost and the vacancy rate of the loading of the AGV delivery car as the optimization goal,the optimization model of multi-target,multi-frequency,and small batch material distribution period is built.According to the characteristics of the model decision variable,the multi-target grey wolf optimization algorithm that improves the group initialization generation and improves the convergence factor has been designed,which improves the ability of algorithm and convergence.Examples verify the feasibility and effectiveness of the model and algorithm.The results of the study show that before optimization,the total distribution cost is reduced by 21.3%,and the average distribution interval is shortened by 23.4%,reducing the backlog and waste of inventory,the optimization of multi-variety material distribution period,and effectively reduced the total delivery cost.

关 键 词：农机制造 混流生产 配送期量 线边配送 多目标灰狼优化算法 

分 类 号：F252.14[经济管理—国民经济]