物流配送客户时间窗变动干扰管理研究

Study on Disruption Management for Customer Time Window Changes in Logistics
【中文摘要】 在物流配送过程中经常发生的对正常物流配送产生干扰和不良影响事件中,有一类干扰是来自于顾客方面的不确定性,表现

为顾客取消需求,新的顾客提出服务请求,顾客突然提出了提前或延后交货、变动交货地点或者改变了需求量等。该干扰事件的出现不仅改

变了该顾客的配送计划,还将对后续的顾客点产生连锁影响,即该路径上的所有剩余任务都将受到该干扰事件的影响。对此,企业必须快速

响应顾客需求改变,迅速制定出对应的调整方案,并希望在尽量降低对整个系统的扰动的前提下,使产生的费用增加最小。干扰管理作为一

种实时处理干扰事件的方法论,主要针对经常性干扰事件的处理和管理。本文正是基于干扰管理这一新理念,针对客户时间窗变动问题扰动

恢复模型及其算法进行了研究。本文的主要工作如下:(1)在对客户时间窗变动干扰辨识的基础上,对扰动进行了度量分析,考虑在途运力与

资源,给出了车辆调度的扰动恢复策略及扰动度量方法。(2)根据本文所提出的扰动度量方法及扰动恢复策略,根据物流企业的实际情况,限

定车场内的车辆数目,采用混合时间窗,从设定虚拟单车场与虚拟多车场两个角度,分别构建了客户时间窗变动扰动恢复模型,这是本文研究

的核心。(3)根据模型的特点与干扰管理思想,改进了基于客户的编码表示方法,构造了相应的遗传算法;并设计了一种新的约束处理方法。

(4)设计了测试实验,对本文提出的扰动恢复模型及算法的有效性进行了验证。本文给出了客户时间窗变动的扰动恢复策略,可以指导设计

VRPTW其他扰动恢复策略;通过设定虚拟单车场或虚拟多车场,将干扰发生在途车辆的起点复位到车场,使VRPTW求解算法同样可以用于处理

扰动恢复模型;对客户时间窗变动对系统造成的干扰进行了度量,为VRPTW其他扰动度量提供了指导;设计了一种新的约束处理方法,避免了

惩罚策略中选取惩罚因子的困难,使得约束处理问题简单化。

【英文摘要】 On the background that frequent disruptions occur in the logistics,there is a kind of disruption,which is

caused by the request changes of customers,such as,new requests by the new customers,requests cancelling,service in

advance/lingeringly,and demand changes,and when they occur,not only the customers disrupted are not serviced according

to the plan,but also the customers in succession to them are affected.In practice,the adjustment plan must be made

quickly to tackle request changes of customers,minimizing increased cost under the premise of the least disruption on

the original plan.As a methodology of handling disruptions in real time,disruption management chiefly settles such kind

of incidents that happens frequently.Based on the concept of disruption management,the recovery model and its algorithm

for customer time window disruption are constructed.The main researches in this paper are as follows:(1)Based on

identifying the customer time window disruption,the deviation measurement is analyzed,and the recovery strategy for the

customer time window disruption is proposed.(2)On the basis of the methods of deviation measurement and recovery

strategy,the recovery model for customer time window disruption is constructed respectively,from setting the single

dummy depot and the multiple dummy depots.This is the core of the paper.(3)According to the characteristic of the model

and the disruption management,the chromosome code based on customer is ameliorated,the genetic algorithm is given,and a

new handling constraint method based on genetic algorithm is designed.(4)The testing experiment is designed,to validate

the recovery model and its algorithm for customer time window disruption.The recovery strategy for the customer time

window disruption is given,to guide to design the other recovery strategy for the VRPTW disruption;By setting the single

dummy depot or the multiple dummy depots,the transition that the jump-offs of vehicles on the way are reposited to the

depot is proposed,making the algorithm for the VRPTW solve the disruption recovery model as before;the customer time

window disruption is analyzed,to help measure the other deviation for VRPTW;A new handling constraint method based on