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物流配送客戶時間窗變動干擾管理研究
Study on Disruption Management for Customer Time Window Changes in Logistics
【中文摘要】 在物流配送過程中經(jīng)常發(fā)生的對正常物流配送產(chǎn)生干擾和不良影響事件中,有一類干擾是來自于顧客方面的不確定性,表現(xiàn)
為顧客取消需求,新的顧客提出服務(wù)請求,顧客突然提出了提前或延后交貨、變動交貨地點或者改變了需求量等。該干擾事件的出現(xiàn)不僅改
變了該顧客的配送計劃,還將對后續(xù)的顧客點產(chǎn)生連鎖影響,即該路徑上的所有剩余任務(wù)都將受到該干擾事件的影響。對此,企業(yè)必須快速
響應(yīng)顧客需求改變,迅速制定出對應(yīng)的調(diào)整方案,并希望在盡量降低對整個系統(tǒng)的擾動的前提下,使產(chǎn)生的費用增加最小。干擾管理作為一
種實時處理干擾事件的方法論,主要針對經(jīng)常性干擾事件的處理和管理。本文正是基于干擾管理這一新理念,針對客戶時間窗變動問題擾動
恢復(fù)模型及其算法進行了研究。本文的主要工作如下:(1)在對客戶時間窗變動干擾辨識的基礎(chǔ)上,對擾動進行了度量分析,考慮在途運力與
資源,給出了車輛調(diào)度的擾動恢復(fù)策略及擾動度量方法。(2)根據(jù)本文所提出的擾動度量方法及擾動恢復(fù)策略,根據(jù)物流企業(yè)的實際情況,限
定車場內(nèi)的車輛數(shù)目,采用混合時間窗,從設(shè)定虛擬單車場與虛擬多車場兩個角度,分別構(gòu)建了客戶時間窗變動擾動恢復(fù)模型,這是本文研究
的核心。(3)根據(jù)模型的特點與干擾管理思想,改進了基于客戶的編碼表示方法,構(gòu)造了相應(yīng)的遺傳算法;并設(shè)計了一種新的約束處理方法。
(4)設(shè)計了測試實驗,對本文提出的擾動恢復(fù)模型及算法的有效性進行了驗證。本文給出了客戶時間窗變動的擾動恢復(fù)策略,可以指導(dǎo)設(shè)計
VRPTW其他擾動恢復(fù)策略;通過設(shè)定虛擬單車場或虛擬多車場,將干擾發(fā)生在途車輛的起點復(fù)位到車場,使VRPTW求解算法同樣可以用于處理
擾動恢復(fù)模型;對客戶時間窗變動對系統(tǒng)造成的干擾進行了度量,為VRPTW其他擾動度量提供了指導(dǎo);設(shè)計了一種新的約束處理方法,避免了
懲罰策略中選取懲罰因子的困難,使得約束處理問題簡單化。
【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
genetic algorithm is designed,avoiding the difficulty of selecting the penalty factor in penalty strategy and makes the
handling constrain simplify.
【中文關(guān)鍵詞】 客戶時間窗變動; 車輛路徑問題; 干擾管理; 擾動恢復(fù); 遺傳算法
【英文關(guān)鍵詞】 Customer Time Window Disruption; Vehicle Routing Problem; Disruption Management; Disruption and Recovery;
Genetic Algorithm
【畢業(yè)論文目錄】
摘要 4-5
Abstract 5-6
1.緒論 9-16
1.1 問題的提出 9-10
1.2 國內(nèi)外同類研究綜述 10-15
1.2.1 干擾管理的國內(nèi)外研究進展 10-12
1.2.2 車輛路徑問題的干擾處理方法研究 12-14
1.2.3 客戶時間窗變動問題的研究現(xiàn)狀 14-15
1.3 本文的主要工作和結(jié)構(gòu) 15-16
2 客戶時間窗變動擾動恢復(fù)模型 16-37
2.1 原始問題描述及其數(shù)學(xué)模型 17-18
2.1.1 原始問題描述 17
2.1.2 原始問題的數(shù)學(xué)模型 17-18
2.2 客戶時間窗變動的擾動恢復(fù)前提與假設(shè) 18
2.3 客戶時間窗變動干擾辨識 18-20
2.4 客戶時間窗變動的擾動恢復(fù)策略 20-21
2.5 虛擬單車場的客戶時間窗變動擾動恢復(fù)模型 21-29
2.5.1 干擾發(fā)生在途車輛的起點復(fù)位到虛擬單車場的轉(zhuǎn)化方法 21-24
2.5.2 擾動度量分析 24-26
2.5.3 虛擬單車場的客戶時間窗變動擾動恢復(fù)模型 26-28
2.5.4 擾動恢復(fù)模型與原始問題的歸一化處理 28-29
2.6 虛擬多車場的客戶時間窗變動擾動恢復(fù)模型 29-36
2.6.1 干擾發(fā)生在途車輛的起點復(fù)位到虛擬多車場的轉(zhuǎn)化方法 29-30
2.6.2 擾動度量分析 30-33
2.6.3 虛擬多車場的客戶時間窗變動擾動恢復(fù)模型 33-35
2.6.4 擾動恢復(fù)模型與原始問題的歸一化處理 35-36
2.7 本章小結(jié) 36-37
3 算法 37-47
3.1 擾動恢復(fù)策略實施 37-39
3.1.1 虛擬單車場的客戶時間窗變動擾動恢復(fù)策略實施 37-39
3.1.2 虛擬多車場的客戶時間窗變動擾動恢復(fù)策略實施 39
3.2 遺傳算法 39-46
3.2.1 遺傳算法的基本步驟 40-41
3.2.2 染色體表示 41-43
3.2.3 違反約束的處理及適應(yīng)度函數(shù)的確定 43-44
3.2.4 遺傳操作 44-45
3.2.5 種群初始化 45-46
3.3 本章小結(jié) 46-47
4 模型與算法驗證 47-51
4.1 數(shù)值實驗及結(jié)果分析 47-48
4.2 各顧客點時間窗變動情況 48
4.3 各配送點時間窗變動后重新調(diào)度的結(jié)果 48
4.4 車輛調(diào)度干擾管理優(yōu)化結(jié)果 48-50
4.5 結(jié)果分析 50-51
結(jié)論 51-52
參考文獻 52-56
附錄A 部分程序源代碼 56-71
攻讀碩士學(xué)位期間發(fā)表學(xué)術(shù)論文情況 71-72
致謝 72-73
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