本文選題：LRP模型　切入點(diǎn)：同時(shí)送取貨　出處：《華南理工大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：選址-路徑問題(LRP)同時(shí)解決了企業(yè)戰(zhàn)略層的設(shè)施選址和運(yùn)作層的車輛調(diào)度兩種互相聯(lián)系的復(fù)雜的決策問題，合理配置運(yùn)力資源，令物流系統(tǒng)總成本最小，達(dá)到系統(tǒng)最優(yōu)，在電子商務(wù)時(shí)代和綠色供應(yīng)鏈環(huán)境下的集成化物流配送網(wǎng)絡(luò)規(guī)劃中具有重要意義。 在實(shí)際物流配送中，顧客常同時(shí)存在送貨和取貨兩種需求，客戶彈性的預(yù)約配送時(shí)間偏好對(duì)客戶滿意度也存在影響。為進(jìn)一步完善和優(yōu)化集成物流配送系統(tǒng)，本文分析電子商務(wù)選址決策和運(yùn)輸管理存在的問題，結(jié)合物流供應(yīng)鏈系統(tǒng)規(guī)劃與設(shè)計(jì)的發(fā)展趨勢(shì)，在選址路徑規(guī)劃模型中結(jié)合顧客對(duì)需求的多樣性以及時(shí)間不確定性，以關(guān)注長(zhǎng)期效益的物流成本最小和客戶滿意度最大為雙目標(biāo)要求。論文主要從以下方面對(duì)選址路徑問題進(jìn)行了分析和研究： 運(yùn)用非線性混合整數(shù)規(guī)劃理論，在倉(cāng)庫(kù)容量限制和路徑容量約束的基礎(chǔ)上，考慮客戶同時(shí)存在送貨和取貨需求的情況和客戶可配送模糊時(shí)間范圍約束的情況，建立基于模糊時(shí)間窗的同時(shí)送取貨的多倉(cāng)庫(kù)、多車型選址路徑模型。 模型求解算法上，本文設(shè)計(jì)結(jié)合模擬退火算法的改進(jìn)兩階段自適應(yīng)遺傳算法進(jìn)行求解。第一階段改進(jìn)混合遺傳算法分別對(duì)初始種群生成方式、遺傳操作和重組策略進(jìn)行改進(jìn)，實(shí)現(xiàn)了模擬退火的良好局部搜索能力與遺傳算法的全局搜索能力的有效結(jié)合。第二階段設(shè)計(jì)模糊優(yōu)化程序，以在最大可容忍時(shí)間窗內(nèi)最大化客戶服務(wù)水平。 最后進(jìn)行數(shù)值實(shí)驗(yàn)，，通過算例驗(yàn)證了模型和改進(jìn)算法的可行性和有效性。仿真實(shí)驗(yàn)表明：兩階段改進(jìn)混合遺傳算法能夠在短時(shí)間內(nèi)給出滿意解，模型有效平衡了客戶服務(wù)水平和物流成本兩個(gè)指標(biāo)，可為實(shí)際的選址與運(yùn)輸決策提供重要參考依據(jù)。 本研究對(duì)拓展選址路徑問題理論和應(yīng)用實(shí)際，改進(jìn)啟發(fā)式求解算法，指導(dǎo)決策者實(shí)踐，促進(jìn)選址與運(yùn)輸決策的科學(xué)化有一定的理論和現(xiàn)實(shí)意義。
[Abstract]:LRP) simultaneously solves the complex decision-making problems of facility location in strategic level and vehicle scheduling in operation layer. Rational allocation of transportation resources can minimize the total cost of logistics system and achieve the optimal system. It is of great significance in the planning of integrated logistics distribution network under the environment of electronic commerce and green supply chain. In order to perfect and optimize the integrated logistics delivery system, customers often have two kinds of demand, delivery and delivery, and customer's flexible preemptive delivery time preference also affects customer satisfaction in the actual logistics distribution. This paper analyzes the problems existing in E-commerce location decision and transportation management, combined with the development trend of logistics supply chain system planning and design, combined with the diversity of customer demand and uncertainty of time in the location path planning model. In order to focus on the long-term benefits of the minimum logistics costs and maximum customer satisfaction as a two-objective requirement. This paper mainly from the following aspects of the location path problem analysis and research:. Based on the constraints of storage capacity and path capacity, the nonlinear mixed integer programming theory is used to consider the situation that the customer has both the demand for delivery and the delivery of goods and the fuzzy time range constraint for customer distribution. A multi-warehouse and multi-vehicle location path model based on fuzzy time window is established. In the model solving algorithm, this paper designs an improved two-stage adaptive genetic algorithm combined with simulated annealing algorithm to solve the problem. In the first stage, the improved hybrid genetic algorithm improves the initial population generation method, genetic operation and recombination strategy, respectively. The good local search ability of simulated annealing is effectively combined with the global search ability of genetic algorithm. In the second stage, a fuzzy optimization program is designed to maximize the level of customer service in the maximum tolerable time window. Finally, numerical experiments are carried out to verify the feasibility and effectiveness of the model and the improved algorithm. The simulation results show that the two-stage improved hybrid genetic algorithm can give a satisfactory solution in a short time. The model effectively balances the customer service level and logistics cost, and can provide an important reference for the actual location selection and transportation decision. This study has certain theoretical and practical significance for expanding the theory and application of location routing problem, improving heuristic algorithm, guiding the practice of decision makers, and promoting the scientific decision of location and transportation.
【學(xué)位授予單位】：華南理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP301.6;F252

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