摘要
针对干扰事件导致易逝品物流配送难以顺利实施这一难题,运用干扰管理思想,结合行为科学中关于消费行为的研究方法对客户进行分类,将物流配送干扰管理问题分为两个阶段:第一阶段处理优先服务的客户,第二阶段处理一般服务的客户;进而构建两阶段的、多目标的干扰管理模型,并提出改进的蚁群算法进行求解。实验结果表明,本文方法虽然配送成本较高,但是却完成了较重要客户的配送任务,这有利于较大幅度提高企业的潜在效益,进而验证了在处理易逝品物流配送干扰问题上的有效性。
It is difficult to continue to carry out the original plan effectively when the disruption occurs in logistic distribution of perishable goods. Based on disruption management, this research aims to improve the science of the decision making by combining the consumption behavior in behavioral science with the quantitative analysis in operations research. At the beginning, the customers are segmented from the following three aspects： recency, purchase frequency and average purchase amount. Then, the problem of disruption management is divided into two stages： the first stage is to handle the customers with priority service and the second stage is to handle the customers with normal service. Furthermore, a model of disruption management characteristic of two-stage and multi-objective is formed and an improved ant colony optimization is put forward to solve the above model. The computational test shows that although it requires the higher cost, our approach finishes the task of the more important customer. The result proves that our approach is helpful to improve the potential profit of enterprise for minimizing the system deviation in logistic distribution.
作者
丁秋雷
胡祥培
姜洋
胡润波
DING Qiu-lei HU Xiang-pei JIANG Yang HU Run-bo(School of Business Administration, Dongbei University of Finance and Economics, Dalian 116025, China Institute of Systems Engineering, Dalian University of Technology, Dalian 116023, China School of Light Industry ＆ Chemical Engineering, Dalian Polytechnic University, Dalian 116034, China China Basiness Executives Acabemy , Dalian 116023, China)
出处
《运筹与管理》
CSSCI
CSCD
北大核心
2016年第6期68-74,共7页
Operations Research and Management Science
基金
国家自然科学基金(71301020
71272093)
教育部哲学社会科学研究重大课题攻关项目(12JZD025)
辽宁省教育厅优秀人才项目(WJQ2014030)
辽宁省教育厅科学研究一般项目(L2014216)
关键词
物流配送
干扰管理
消费行为
易逝品
logistic distribution
disruption management
consumption behavior
perishable goods
