本文關(guān)鍵詞： 車輛路徑問題 配送地點變化 干擾管理 蟻群算法　出處：《杭州電子科技大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：當(dāng)今電子商務(wù)正在飛速發(fā)展和普及,物流配送成為了影響電子商務(wù)發(fā)展至關(guān)重要的一個環(huán)節(jié),車輛路徑問題便是研究如何規(guī)劃配送路線的問題。然而在實際配送過程中,配送車輛會遇到一系列未知的干擾事件,如客戶需求量變化、配送地點變化、交通事故、天氣變化等,使得車輛無法繼續(xù)按照原有配送方案執(zhí)行任務(wù),因此需要快速的生成一個調(diào)整方案,來指導(dǎo)車輛應(yīng)對這些未知問題。目前,動態(tài)車輛路徑問題便是針對這一問題所開展的研究,但是調(diào)整策略往往只是以配送費用最低為目標(biāo)來重新規(guī)劃路線,卻忽略了客戶與配送員的利益。因此,本文結(jié)合上述問題和目前車輛路徑問題的研究現(xiàn)狀,運用干擾管理思想,來制定新的調(diào)整方案,以滿足客戶、配送員、物流公司三方面的需求。首先,本文結(jié)合車輛路徑問題和實際研究需要,設(shè)計了初始配送問題,并根據(jù)問題假設(shè),建立了初始配送模型。選取客戶配送地點發(fā)生變化這一現(xiàn)象作為干擾事件,分別從客戶、物配送員,物流公司三個角度分析客戶配送地點發(fā)生變化給配送計劃帶來的擾動,進(jìn)行相應(yīng)度量方法設(shè)計。以此構(gòu)建了基于客戶不滿意度低、物流公司配送成本少、配送路線偏離程度最小的多目標(biāo)配送干擾管理模型。其次,為了達(dá)到快速模型求解,滿足實際應(yīng)用需求的目的,本文選取蟻群算法進(jìn)行問題求解。由于蟻群算法存在一些缺陷和不足,本文主要從轉(zhuǎn)移概率函數(shù)、信息素更新策略和局部優(yōu)化三個方面進(jìn)行改進(jìn)設(shè)計�？紤]到算法參數(shù)影響,本文以初始配送問題為研究對象,通過仿真實驗確定蟻群算法關(guān)鍵性參數(shù)的取值。最后,為了驗證模型和求解算法的有效性和實用性,本文在MATLAB軟件上,通過算例求解分別與遺傳算法、退火算法、混合粒子群算法進(jìn)行比較分析,驗證算法性能的高效性。通過與重調(diào)度法進(jìn)行對比,表明本文路線調(diào)整策略的可行性和有效性。本文提出的基于配送地點變化的物流路徑優(yōu)化策略,可以有效的兼顧多方利益,生成擾動較小配送方案,對動態(tài)車輛路徑問題、干擾管理、啟發(fā)式算法方面的研究有一定的參考價值。
[Abstract]:Nowadays, electronic commerce is developing rapidly and popularizing. Logistics distribution has become a crucial link that affects the development of electronic commerce. The vehicle routing problem is to study how to plan the distribution route. However, in the actual distribution process, the distribution vehicle will encounter a series of unknown interference events, such as the change of customer demand and the change of distribution location. Traffic accidents, weather changes and so on, make the vehicle can not continue to carry out the tasks according to the original distribution plan, so it is necessary to quickly generate an adjustment scheme to guide the vehicle to deal with these unknown problems. The dynamic vehicle routing problem is a research on this problem, but the adjustment strategy is usually aimed at the lowest distribution cost to re-plan the route, but ignore the interests of the customer and the distributor. This paper combines the above problems and the current research status of vehicle routing problem, using the idea of interference management, to formulate a new adjustment scheme to meet the customer, distribution staff, logistics company three aspects of the needs. First of all. Combined with the vehicle routing problem and the actual research needs, this paper designs the initial distribution problem, and establishes the initial distribution model according to the assumption of the problem. The phenomenon of customer distribution location change is selected as the interference event. From three angles of customer, material distributor and logistics company, this paper analyzes the disturbance caused by the change of customer distribution location to the distribution plan, and designs the corresponding measurement method to construct the low customer dissatisfactory degree. The multi-objective distribution interference management model with less cost and minimum deviation of distribution route. Secondly, in order to solve the model quickly, to meet the needs of practical applications. In this paper, ant colony algorithm is selected to solve the problem. Due to some shortcomings and shortcomings of ant colony algorithm, this paper mainly from the transfer probability function. The pheromone updating strategy and local optimization are improved. Considering the influence of algorithm parameters, this paper takes the initial distribution problem as the research object. Finally, in order to verify the effectiveness and practicability of the model and the algorithm, this paper is on the MATLAB software. The algorithm is compared with genetic algorithm, annealing algorithm and hybrid particle swarm optimization algorithm to verify the efficiency of the algorithm, and compared with the rescheduling method. The results show that the route adjustment strategy is feasible and effective. The logistics route optimization strategy based on the change of distribution location can effectively take into account the interests of many parties and generate a less disturbance distribution scheme. The research on dynamic vehicle routing problem, disturbance management and heuristic algorithm has some reference value.
【學(xué)位授予單位】：杭州電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F252

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