【摘要】：物流配送是物流最重要的環(huán)節(jié),它在整個(gè)物流體系中發(fā)揮著重要的作用,諸如完善物流系統(tǒng)、提高物流效益、降低物流庫(kù)存等。物流配送在實(shí)踐發(fā)展中越來(lái)越重要,企業(yè)的發(fā)展已經(jīng)離不開(kāi)它,只有合理高效的物流配送才能提高顧客滿意度及企業(yè)物流的效率和效益,達(dá)到企業(yè)和顧客的雙贏。在實(shí)際物流配送過(guò)程中,常常受到一系列不確定因素的影響,如交通管理、交通流量、天氣變化、交通事故、車輛堵塞等,造成物流配送延遲,使原有的物流配送計(jì)劃受到影響,從而影響企業(yè)的物流效率及顧客的滿意度;當(dāng)出現(xiàn)這種問(wèn)題時(shí),為了提高顧客滿意度,必須有效的解決這類干擾問(wèn)題。如何有效的處理這些不確定因素,使得不利影響降到最低成為物流界研究的難點(diǎn)問(wèn)題。針對(duì)上述不確定性突發(fā)事件,本文引入干擾管理的概念,來(lái)解決物流配送過(guò)程中發(fā)生的各種干擾事件,干擾管理思想即是針對(duì)突發(fā)的、難以預(yù)測(cè)的狀況,在所要建立的模型中加入相應(yīng)的約束條件和優(yōu)化目標(biāo),另外采用高效的求解算法,迅速、高效地處理干擾事件,得出最有效的路徑調(diào)整計(jì)劃。干擾管理中所講的路徑計(jì)劃調(diào)整并不同于傳統(tǒng)的擾動(dòng)發(fā)生時(shí)完全徹底的調(diào)整已有計(jì)劃來(lái)重新建模和優(yōu)化,不同的是,干擾管理是以干擾發(fā)生后的狀態(tài)為基礎(chǔ),只針對(duì)剩余未配送客戶進(jìn)行調(diào)整以求對(duì)系統(tǒng)擾動(dòng)最小。本文正是以這一理念為基礎(chǔ),建立了有顧客時(shí)間窗變化的、物流配送延遲的干擾管理模型,以系統(tǒng)擾動(dòng)最小為目標(biāo),采用多種群遺傳算法,在干擾發(fā)生時(shí),通過(guò)局部調(diào)整來(lái)求得最優(yōu)路徑。本文的主要研究工作如下:(1)在具體描述有顧客時(shí)間窗的物流配送延遲問(wèn)題的基礎(chǔ)上,提出顧客滿意度最高、配送路徑延遲時(shí)間最小兩個(gè)目標(biāo),并提出解決這兩個(gè)問(wèn)題的思路。(2)根據(jù)本文所提出的兩個(gè)目標(biāo),建立有顧客時(shí)間窗的物流配送延遲的干擾管理模型。(3)運(yùn)用多種群遺傳算法對(duì)干擾管理模型進(jìn)行求解,找出有顧客時(shí)間窗的物流配送延遲的最優(yōu)調(diào)整策略。(4)根據(jù)文章提出的物流配送延遲干擾管理模型,結(jié)合A公司配送延遲的具體實(shí)例,驗(yàn)證了模型及算法的有效性。本文所研究的有顧客時(shí)間窗的物流配送延遲的干擾管理問(wèn)題,大大提高了物流配送效率,增加了顧客的滿意度,減小了物流配送的成本。為干擾管理問(wèn)題的進(jìn)一步研究提供了基礎(chǔ)和借鑒。
[Abstract]:Logistics distribution is the most important link of logistics, it plays an important role in the whole logistics system, such as perfecting logistics system, improving logistics benefit, reducing logistics inventory and so on. Logistics distribution is more and more important in practice, and the development of enterprise can not be separated from it. Only reasonable and efficient logistics distribution can improve the customer satisfaction and the efficiency and benefit of enterprise logistics, and achieve the win-win of enterprise and customer. In the actual logistics distribution process, it is often affected by a series of uncertain factors, such as traffic management, traffic flow, weather changes, traffic accidents, vehicle congestion and so on, which results in the delay of logistics delivery. The original logistics distribution plan will be affected, thus affecting the logistics efficiency of enterprises and customer satisfaction; When this kind of problem occurs, in order to improve customer satisfaction, this kind of interference problem must be solved effectively. How to deal with these uncertainties effectively to minimize the adverse impact becomes a difficult problem in logistics research. In view of the above-mentioned uncertain emergencies, this paper introduces the concept of interference management to solve all kinds of interference events in the process of logistics distribution. The idea of interference management is aimed at the sudden and difficult to predict the situation. The corresponding constraints and optimization objectives are added to the model to be established. In addition, the efficient algorithm is used to deal with the interference events quickly and efficiently, and the most effective path adjustment plan is obtained. The path planning adjustment mentioned in interference management is different from the complete and complete adjustment of the existing plan to remodel and optimize when the traditional disturbance occurs, but the interference management is based on the state after the disturbance occurs. Only for the remaining undelivered customers to adjust to minimize the system disturbance. In this paper, based on this idea, the interference management model with customer time window change and logistics delivery delay is established. In order to minimize the disturbance of the system, multi-population genetic algorithm is adopted when the disturbance occurs. The optimal path is obtained by local adjustment. The main research work of this paper is as follows: (1) on the basis of describing the delay problem of logistics delivery with customer time window, the paper puts forward two goals: the highest customer satisfaction and the least delay time of distribution path. (2) according to the two objectives proposed in this paper, the interference management model of logistics delivery delay with customer time window is established. (3) Multi-group genetic algorithm is used to solve the interference management model. Find out the optimal adjustment strategy of logistics distribution delay with customer time window. (4) according to the management model of logistics distribution delay interference proposed in this paper, the validity of the model and algorithm is verified by a concrete example of A company delivery delay. In this paper, the interference management of logistics distribution delay with customer time window is studied, which greatly improves the efficiency of logistics distribution, increases customer satisfaction and reduces the cost of logistics distribution. It provides a basis and reference for further research on interference management.
【學(xué)位授予單位】：蘭州財(cái)經(jīng)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：F259.2

【參考文獻(xiàn)】

相關(guān)期刊論文 前8條

1 潘震東;唐加福;韓毅;;帶貨物權(quán)重的車輛路徑問(wèn)題及遺傳算法[J];管理科學(xué)學(xué)報(bào);2007年03期

2 肖鵬,李茂軍,張軍平,童調(diào)生;車輛路徑問(wèn)題的單親遺傳算法[J];計(jì)算技術(shù)與自動(dòng)化;2000年01期

3 趙春閣;徐群;;有顧客時(shí)間窗的物流配送干擾管理研究[J];湖南商學(xué)院學(xué)報(bào);2014年03期

4 黃崇超;于剛;汪嵩;王先甲;;DISRUPTION MANAGEMENT FOR SUPPLY CHAIN COORDINATION WITH EXPONENTIAL DEMAND FUNCTION[J];Acta Mathematica Scientia;2006年04期

5 王明春;高成修;曾永廷;;VRPTW的擾動(dòng)恢復(fù)及其TABUSEARCH算法[J];數(shù)學(xué)雜志;2006年02期

6 姜大立,楊西龍,杜文,周賢偉;車輛路徑問(wèn)題的遺傳算法研究[J];系統(tǒng)工程理論與實(shí)踐;1999年06期

7 王旭坪;楊德禮;許傳磊;;有顧客需求變動(dòng)的車輛調(diào)度干擾管理研究[J];運(yùn)籌與管理;2009年04期

8 王洪剛;馬良;;TSP的量子螞蟻算法求解[J];運(yùn)籌與管理;2009年06期

相關(guān)博士學(xué)位論文 前2條

1 謝秉磊;隨機(jī)車輛路徑問(wèn)題研究[D];西南交通大學(xué);2003年

2 張建勇;模糊信息條件下車輛路徑問(wèn)題研究[D];西南交通大學(xué);2004年

相關(guān)碩士學(xué)位論文 前1條

1 張漪;物流配送受擾延遲問(wèn)題的干擾管理模型研究[D];大連理工大學(xué);2007年

，

本文編號(hào)：2432835