论文总字数：26409字

摘 要

近年来，中国的服务业也随着时代进步不断地飞速发展，而在许许多多的服务业中，物流配送路线优化都是无法绕开的一个重要的问题。在相当一部分服务业企业中，都会遇到这样的一些问题：旗下门店分布广泛，门店营业面积小，储存运输设备能力不足，储存运输速度不足等。而旗下产品对储存运输的空间与环境要求高，门店不具备长期储存能力。那么，如何在物流配送路线优化上做到准时，高效，安全，准确，是企业提升服务质量并降低企业成本所需要解决的一个重要问题，也是企业如何能够科学管理方法和长期稳定运转的制胜秘诀，科学合理的物流配送路线规划对于物流问题中的储存运输作业来说不可或缺。

为解决这类物流配送路线管理的优化问题，本文先从武汉市某新兴连锁便利店集团（以下简称L公司）所存在的同城物流配送路线优化问题分析出发，对实际问题中的车辆的安排以及车辆的配送路线问题进行深入研究，将车辆行驶总路程最低作为第一优化目标，配送车辆数量最少作为第二优化目标，并考虑配送时间，单位车辆装载上限的约束条件，最后建立该问题的数学模型。通过分析当下学术界处理该类问题所应用到的各种方法，选取了其中最为常用到的两种方法：贪心算法，节约里程法。使用这两种方法，对该数学模型进行分析解读并得出优化分析结论，使得配送路线得到优化，运输总里程得以下降，配送速度提升，运输所需车辆数量下降。以达到提高配送效率，降低配送成本，并能够提升物流服务质量，增加企业利润等目的。

本文对于物流行业中最为常见的配送路线优化问题进行了研究，意在提高客户满意度，降低配送花费的时间，提升配送效率并降低配送中产生的成本，解决部分中小企业中所存在的物流配送路线规划不够科学严谨，服务意识落后，服务质量一般等问题。

研究结果表明，物流配送路线的优化确实有利于企业管理效率的提升，物流配送路线的信息化有利于企业管理的科学化规划化，这样对企业资源的科学规范地统一调动有利于企业管理水平的提高。

关键词：配送路线优化；贪心算法；节约里程法；管理

Abstract（Time New Roman粗体小二号）

In recent years, China's service industry has also been developing rapidly with the

progress of the times, and in many service industries, the optimization of logistics distribution routes is an important issue that cannot be bypassed. In a considerable part of the service industry enterprises, such problems will be encountered: their stores are widely distributed, the business area of ​​the stores is small, the storage and transportation equipment capacity is insufficient, and the storage and transportation speed is insufficient. However, its products have high requirements for storage and transportation space and environment, and the stores do not have long-term storage capabilities. So, how to achieve punctuality, efficiency, safety, and accuracy in the optimization of logistics distribution routes is an important problem that companies need to solve to improve service quality and reduce enterprise costs. It is also the secret of how companies can achieve scientific management methods and long-term stable operation. , Scientific and reasonable logistics distribution route planning is indispensable for storage and transportation operations in logistics problems.

In order to solve this kind of logistics distribution route optimization problem, this

article starts with the analysis of the same city logistics distribution route optimization problem existing in an emerging chain convenience store group in Wuhan (hereinafter referred to as L company), and the vehicle allocation and distribution route problems in the actual problem Carrying out in-depth research, taking the lowest total distance of vehicles as the first optimization goal, using the lowest number of vehicles as the second optimization goal, and considering the constraints of delivery time and the upper limit of the unit vehicle loading upper limit, the mathematical model of the problem is finally established. By analyzing the various methods applied by the current academic community to deal with such problems, two of the most commonly used methods are selected: the greedy algorithm and the mileage saving method. Using these two methods, the mathematical model is analyzed and interpreted and the conclusion of the optimization analysis is obtained, so that the distribution route is optimized, the total mileage of the transportation is reduced, the distribution speed is increased, and the number of vehicles required for transportation is reduced. Eventually, the purpose of reducing distribution costs, improving distribution efficiency, improving distribution service quality and increasing profits is achieved.

This paper studies the most common distribution route optimization problems in

the logistics industry, aimed at improving customer satisfaction, reducing distribution time, improving distribution efficiency and reducing distribution costs, and solving the logistics distribution route planning in some SMEs that is not scientifically rigorous , Backward service awareness, general service quality and other issues.

The results of the study show that the optimization of the logistics distribution route

is indeed conducive to the improvement of enterprise management efficiency. The informationization of the logistics distribution route is conducive to the scientific planning of enterprise management. In this way, the scientific and standardized unified mobilization of enterprise resources is conducive to improve the level of enterprise management.

Key Words： Distribution Route Optimization; Greedy Algorithm; Saving Algorithm; Management

目 录

第1章 绪论 8

1.1 研究背景 8

1.2 研究目的及研究意义 9

1.2.1 研究目的 10

1.2.2 研究意义 10

1.3 业内研究现状及相关理论综叙 11

1.4 研究内容及研究方法选取 13

1.4.1 研究内容 13

1.4.2 研究方法选取 13

第2章 L公司产品配送路线管理现状 15

2.1 L公司产品配送路线管理现状与存在的问题 15

2.2 L公司产品配送路线规划问题建模 16

2.2.1 问题描述 16

2.2.2 数学模型的构建 17

2.3 节约里程法的算法原理与应用步骤 17

2.3.1 算法原理 17

2.3.2 应用步骤 18

2.4 贪心算法的原理与应用步骤 19

2.4.1 算法原理 19

2.4.2 应用步骤 19

2.5 本章小结 20

第3章 两种算法在L公司产品配送路线管理中的应用 21

3.1 L公司产品配送路线优化方案设计 21

3.1.1 旗下门店订单需求量数据收集 21

3.1.2 配送路线数据收集 21

3.2 节约里程法在L公司产品配送路线优化中的应用 22

3.3 贪心算法在L公司产品配送路线优化中的应用 24

3.4 本章小结 27

第4章 两种算法对L公司物流配送路线优化效果分析及思考 28

4.1 L公司物流配送路线初始方案分析 28

4.2 两种算法对L公司物流配送路线优化前后对比 28

4.2.1 配送总里程前后对比 28

4.2.2 装载率前后对比 29

4.3 优化算法对L公司物流配送路线的影响与思考 30

4.4 本章小结 31

第5章 结论与展望 32

5.1 结论 32

5.2 展望 32

参考文献 34

致谢 36

第1章 绪论

1.1 研究背景

随着我国科技与经济的飞速发展，社会生产力与人民消费能力也在随之不断提升。与此同时，我国市场的流通规模与流通范围也越来越大，市场对于物流服务的需求也越来越大，要求也越来越高。有需求就有市场，中国物流行业的水平也就水涨船高。根据中国物流与采购联合会发布的统计数据，2014至2019年间，我国社会物流总需求保持着稳定增长的趋势。2020年第一季度，全国物流总额达到了56.0万亿元，2019年全年的全国社会物流总额超过300万亿元。虽然第一季度相对而言，物流市场规模略有收缩，但其中主要原因是疫情。

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