摘要: 近年来,随着生活水平的提高,电子商务逐渐被人们所接受,我国电商市场蓬勃发展,并融入人们日常生活的方方面面。如今对于电商而言,生鲜物流领域既是机遇也是挑战。由于生鲜食品的鲜活性和易腐烂的特点,使得生鲜食品的质量问题不仅靠生产,更需搞好流通,因此优化配送路径,降低冷链运输成本成为制约整个生鲜物流配送过程的关键因素。
本课题首先介绍了我国生鲜物流的发展背景、研究现状及发展趋势,然后分析了文献中路径优化的几种常用方法,最后采用人工蜂群算法研究解决生鲜物流配送路径优化问题。人工蜂群算法是一种模拟蜜蜂采蜜行为的群体智能优化算法,具有参数少、 易于实现、计算简单等优点,为解决复杂全局优化问题提供了一种新的方法。最后利用Matlab软件进行仿真,验证了人工蜂群算法对生鲜物流路径优化的有效性,能为生鲜物流配送带来积极的影响。28688
关键词:生鲜物流 冷链配送 路径优化 人工蜂群算法
毕业设计说明书(毕业论文)外文摘要
Title The application of Artificial colony algorithm in the fresh logistics path optimization problem
Abstract
In recent years, with the improvement of living standards. Electronic commerce is gradually accepted by people, our country electric dealer market is booming,and into all aspects of People's Daily life. Now for the electricity, fresh logistics field is both opportunity and challenge. Because of the fresh food and decay of fresh characteristic make fresh food quality problem not only depends on the production, more need to do a good job in the circulation,optimize the distribution route, therefore, reduce the cold chain transportation costs become the key factor for the whole process of fresh logistics distribution.
This topic firstly introduces the development background of fresh logistics in our country, research status and development trend, and then analyzes the path optimization of several commonly used methods in literature, finally using artificial colony algorithm on the fresh logistics distribution route optimization problem. Artificial bees colony algorithm is a kind of simulation behavior of swarm intelligence optimization algorithm, has the advantages of less parameters、 easy to implement and simple calculation, to solve the complicated optimization problem provides a new method. At last, using the Matlab software simulation result shows that the artificial colony algorithm on the effectiveness of fresh logistics path optimization, can bring positive effect to fresh logistics distribution.
Key Words Fresh logistics Cold chain logistics Path optimization Artificial Bee Colony Algorithm
目 次
1 绪论 1
1.1 研究背景 1
1.2 研究现状 1
1.3 研究内容 2
1.4 研究意义 3
1.5 章节安排 3
2 生鲜物流简介 4
2.1 生鲜电商的发展和现状 4
2.2 生鲜物流的难点 5
2.3 阻碍生鲜电商发展问题的解决方案 7
2.4 国内生鲜电商模式 8
2.5 本章小结 8
3 物流路径优化问题的解决方法 9
3.1 蚁群算法 9
3.2 遗传算法 10
3.3 人工蜂群算法 10
3.4 本章小结 10
4 人工蜂群算法在生鲜物流路径优化问题上的应用 11
4.1 生鲜物流路径优化问题概述 11
4.2 算法实现 11
4.3 仿真验证 12
4.4本章小结15
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