摘 要

我国的柔性制造业在“中国制造2025”的带动下迎来了长足发展，柔性制造系统越来越受到制造行业的青睐，针对如何设计一个柔性可重构的生产系统的研究也越来越多，这是一个具有现实意义和伟大前景的研究课题。在设计一个柔性制造车间时，不可避免地要考虑到设备的布局和路径规划，AGV路径规划依赖于设备布局的结果，而设备布局同样受到路径规划和物料运输的影响，因此，两者具有很强的耦合关系。截止到目前有关设备布局和AGV路径规划的研究，更多是先确定设备布局方案，然后再规划AGV的搬运路径，忽略了两者之间密不可分的联系，从而导致总不能达到现实最优方案，在解决此类问题时，如果可以同时考虑设备布局和路径规划，就能更好地提高系统的柔性，更加合理地优化设计，从而得到更优的解决方案，进一步降低生产的成本。

本文分析了区域式AGV系统设备布局和路径规划的关系，在此基础上建立了对应的以跨环运输量和环内物流量最小为目标的数学模型，模型求解过程分成三个阶段，第一阶段，以最小化跨环运输量为目标，根据已定的回路个数及各设备间的运载量确定设备分组。第二阶段，考虑分配到每个回路的设备的尺寸大小和最小安全距离要求，以最小化环内物流量为确定原则，确定每个回路内的设备布局和AGV搬运路径方案。第三阶段，在已经获得各回路的具体布置结果后，考虑车间的尺寸形状，把各回路布置到生产车间内，并设计转运中心连接各回路，实现跨回路运输，此阶段的设计目标是最小化跨环物流量。本文采用整数编码方式的遗传算法，利用Matlab编程，实现了模型求解，通过实例验证了模型和算法的有效性，具有一定的理论和现实意义。

关键词：设备布局；区域式AGV系统；协同优化；遗传算法

Abstract

China's flexible manufacturing industry has made great strides with "Made in China 2025". Flexible manufacturing systems are more and more favored by the manufacturing industry, and there are more and more researches on how to design a flexible and reconfigurable production system. This is a research topic of practical importance and great prospects. When designing a flexible manufacturing workshops, it is inevitable to consider the layout and path planning of the facility. The AGV path planning depends on the results of the facility layout, and the facility layout is also affected by the path planning and material transportation. Therefore, they have strong Coupling relationship. Most current research studies the two issues independently. After the facility layout is completed, the path planning of the AGV is considered, and the internal relationship between the two is not considered, resulting in the fact that the actual optimal plan cannot always be reached When solving such problems, if the facility layout and path planning can be considered at the same time, the flexibility of the system can be better improved, and the design can be optimized more reasonably, thereby obtaining a better solution and further reducing the cost of production.

This paper analyzes the relationship between the regional AGV system facility layout and path planning. On this basis, a corresponding mathematical model with the goal of cross-loop transportation volume and intra-loop flow is established. The model solution process is divided into three stages. In the first stage, the goal is to minimize the cross-loop traffic, and determine the facility grouping based on the number of circuits that have been determined and the carrying capacity between each facility. In the second stage, considering the size and minimum safety distance requirements of the equipment allocated to each circuit, the principle of minimizing the material flow in the loop is used to determine the equipment layout and AGV transportation path plan in each circuit. In the third stage, after obtaining the specific layout results of each loop, considering the size and shape of the workshop, arrange each loop into the production workshop, and design the transfer center to connect each loop to achieve cross-loop transportation. The design goal of this stage is the lowest Chemical flow across the loop. In this paper, the genetic algorithm with integer coding and Matlab programming are used to successfully solve the model, and a specific example is used to verify the effectiveness of the model and algorithm, which has certain theoretical and practical significance.

Key Words：Facility layout；Tandem AGV system；Collaborative optimization；Genetic algorithm

目 录

摘 要 1

Abstract 2

目 录 4

第1章 绪论 1

1.1 研究背景及意义 1

1.1.1 研究背景 1

1.1.2 研究意义 1

1.2 国内外研究现状 2

1.2.1 设备布局研究现状 2

1.2.2 AGV路径规划研究现状 2

1.2.3 协同优化设备布局和AGV路径规划研究现状 3

1.3 研究内容和思路 3

第2章 模型建立 5

2.1 问题描述 5

2.1.1 设备布局问题 5

2.1.2 区域式AGV路径规划问题 6

2.1.3 协同优化AGV路径规划与设备布局问题 7

2.2 数学模型 7

2.2.1 假设条件 7

2.2.2 符号说明 8

2.2.3 目标函数 8

2.2.4 约束条件 9

2.3 本章小结 10

第3章 求解算法 11

3.1 遗传算法原理和流程 11

3.2 算法要素和操作 12

3.2.1 编码 12

3.2.2 适应度函数设计 12

3.2.3 选择操作 13

3.2.4 交叉操作 13

3.2.5 变异操作 15

3.3 本章小结 16

第4章 问题求解 17

4.1 设备分群 17

4.2 回路布局和路径 19

4.3 回路布置 21

4.4 结果分析、经济性评价 22

4.5 本章小结 23

第5章 总结与展望 24

5.1 全文总结 24

5.2 下一步工作 24

参考文献 25

致 谢 26

绪论

研究背景及意义

研究背景

柔性制造系统^[1] (Flexible Manufacturing Systems)可以适应多加工对象的生产活动，甚至可以同时从事不同种产品的生产，具有自动化水平高、适应性强等一系列优点。柔性制造系统能够更好地适应变化的生产环境和生产操作，在市场需求环境多变的今天，一个生产制造系统必须要有能力应对外部市场环境和内部系统的大幅变化，具备良好的抗干扰性能。

自动导引车（AGV）是一种自动搬运车辆，配备有诸如导轨、磁条和激光之类的供AGV沿着预定路线移动的自动导引装置。具有效率高、安全性能好、易于计算机管理和调度等优点，在制造业中得到了广泛的应用，实现了可重构制造系统中设备之间的关联。在提高生产车间的自动化水平和生产效率上，AGV的应用具有良好的效果，可以使生产系统更加具有灵活性。有关AGV路径规划问题的研究对于柔性智能制造车间具有深远的理论和现实意义。