摘 要

21世纪是信息化高速发展的时代，信息生产与信息处理方式的巨大变革对人们的学习和生活产生了很大的影响，其在教育方面的影响尤为突出。传统学习方式主要是通过纸质书籍、课堂学习、同学交流等方式来获取知识，但是由于信息技术的发展，学习平台、在线教学等互联网学习方式大量涌现，这极大的提高了人们的学习效率、丰富了人们的学习体验。为响应趋势，各大高校都在建立在线学习平台，为学生提供各类学习资源。其中最优化模型课程在一些高校的建模、运筹类在线课程中都有出现，但大多针对理论部分，几乎不涉及模型实现，在教学上理论与实践脱节，课程不能充分满足学生的学习需求。

基于Jupyter的最优化建模学习与实践平台旨在构建在线学习平台帮助学习者更好的掌握最优化模型建模过程。平台根据知识板块可划分为线性规划、非线性规划、二次规划、整数规划、动态规划等五个模块。根据功能板块可划分为学习资料、实操学习、学习测试、个人管理等四个模块。其中实操学习是本平台的核心模块，该模块利用Jupyter这一交互式笔记本展示模型的输入输出，同时利用Python编程语言分步骤展示模型的实现过程，学习者也可根据Jupyter中的操作同步进行操作，从而获得更好的学习体验。

平台开发运用Django Web应用框架，关注模型、模板和视图。数据库开发语言为Sql，利用Sql语言对数据库进行操作。后端开发语言是Python，利用Python来进行逻辑处理与模型实现。前端开发语言为Html、Javascript,支持页面实现。

本系统的特色在于将Jupyter与最优化建模结合起来。首先，虽然最优化模型理论类的资料很多，但是有关模型实现类的资料却极少，该平台利用Python编程实现了最优化模型且有详细资料指导学习者实现最优化建模。其次，Jupyter的交互式特点使得学习者可以将理论学习与练习同步进行，学习者在这种交互式的学习中可以获得更好的学习体验，弥补了在线课程中理论与实践相脱节，并无法实时获得指导的情况。

关键词：Jupyter；最优化模型；实操学习；Django框架；Python语言

Abstract

The 21st century is an era of rapid development of information technology. The tremendous changes in information production and information processing have had a great impact on people's learning and life, and their influence on education is particularly prominent. The traditional learning method mainly acquires knowledge through paper books, classroom learning, classmate exchanges, etc. However, due to the development of information technology, there are a large number of Internet learning methods such as learning platforms and online teaching, which greatly improves people's learning efficiency. Enriched people's learning experience. In response to the trend, universities are setting up online learning platforms to provide students with a variety of learning resources. Among them, the optimization model course has appeared in some colleges' modeling and operation online courses, but they are all aimed at the theoretical part, and almost no model implementation is involved. In theory, the theory and practice are out of line, and the course cannot fully meet the students' learning needs.

Jupyter-based optimization modeling learning and practice platform aims to build a learning platform to help learners better master the optimization model modeling process. According to the knowledge section, the platform can be divided into five modules: linear programming, nonlinear programming, quadratic programming, integer programming, and dynamic programming. According to the function section, it can be divided into four modules: learning materials, practical learning, unit testing, and personal management. The practical learning is the core module of the platform. The module uses the interactive notebook of Jupyter to display the input and output of the model. At the same time, the implementation process of the model is demonstrated step by step using the Python programming language. The learner can also perform the synchronization operation according to the Jupyter. Operate for a better learning experience.

Platform development uses the Django web application framework to focus on models, templates, and views. The database development language is Sql, and the database is operated by using the Sql language. The back-end development language is Python, which uses Python for logical processing and algorithmic implementation of models. The front-end development language is Html, Javascript, and supports page implementation.

The system is characterized by the combination of Jupyter and optimization modeling. First of all, although there are many materials in the optimization model theory class, there is very little information about the model implementation class. The platform uses Python programming to implement the optimization model and has detailed information to guide the learners to achieve optimal modeling. Secondly, Jupyter's interactive features enable learners to synchronize theoretical learning with practice. Learners can gain a better learning experience in this interactive learning, making up for the disconnect between theory and practice in online courses. Get guidance in real time.

Key Words：Jupyter; Optimization model; practical learning; Django framework; Python language

目 录

学位论文原创性声明…………………………………………………………………………….II

学位论文版权使用授权………………………………………………………………………….II

摘 要 …………………………………………………………………………………………. III

Abstract………………………………………………………………………………………….. I

第1章 绪论………………………………………………………………………………………1

1.1 设计的目的 1

1.2 设计的意义 1

1.3 国内外研究现状 2

1.3.1 国内在线教学平台研究现状 2

1.3.2 国内教学工具与Jupyter使用研究现状 2

1.3.3 国外教学中Jupyter使用研究现状 2

1.4 设计内容和设计方法 3

1.4.1 系统目标和基本内容 3

1.4.2 技术方法和措施 3

第2章 系统分析…………………………………………………………………………………5

2.1 需求分析 5

2.2 可行性分析 6

2.2.1 技术可行性 6

2.2.2 经济可行性 6

2.3 业务流程分析 7

2.4 数据流程分析 9

2.5 数据字典 11

2.5.1 外部实体 11

2.5.2 数据流条目 11

2.5.3 数据项描述 12

2.5.4 数据流清单 13

2.5.5 数据存储清单 14

第3章 系统设计………………………………………………………………………………..15

3.1 系统内容设计 15

3.1.1 Jupyter使用教案 15

3.3.2 相关Python使用教案 21

3.3.3 最优化模型 24

3.3.4 基于Jupyter的最优化模型的实现与应用 26

3.2系统总体设计 36

3.2.1 功能模块设计 36

3.2.2 物理配置方案设计 37

3.3 系统详细设计 38

3.3.1 编码设计 38

3.3.2 数据库设计 39

3.3.3 输入输出设计 44

3.3.4 界面设计 45

3.3.5 Jupyter输入输出设计 57

第4章 系统实施………………………………………………………………………………..61

4.1 系统调试 61

4.1.1 编程规范 61

4.1.2 模拟运行系统 61

4.2 系统测试 63

4.2.1 系统测试计划的制定 63

4.2.2 系统测试用例的设计 64

4.2.3 系统测试计划的执行 64

参考文献………………………………………………………………………………………... 66

附录A……………………………………………………………………………………………67

致 谢…………………………………………………………………………………………... 75

第1章 绪论

1.1 设计的目的

对于每一位学习者来说，能否获取有价值的学习资料是一件十分重要的事情。针对学习者在最优化建模学习中面临的资料不系统、实践与理论相脱节的问题，搭建基于Jupyter的最优化建模学习与实践平台是十分有必要的。因此构建该平台的目的表现在以下几个方面：