Implementierung einer GUI-Applikation zur optimalen Zuordnung von Studenten mittels Java/Swing

Table of Contents

1 Project description of JAssign

1.1 Introduction

1.2 System specifications

1.3 Available legacy systems and resources

1.4 Project schedule

1.5 Project Milestones

1.6 Structured plan

2 Creation of a GUI with Java / Swing

2.1 Basic description of Swing

2.2 Commonly used widgets

3 Implementation

3.1 The class structure of JAssign

3.2 External libraries used

3.3 The datatype package

3.4 The functions package

3.5 The optimization package

3.6 The user interface

4 Conclusion

5 Appendix

5.1 The optimization model used

Objectives and Research Focus

The objective of this thesis is the development of a standalone Java application named JAssign, designed to automate the assignment of students to university course projects based on individual student preferences. The research addresses the complexity of manual group formation by utilizing linear optimization algorithms within a user-friendly graphical interface.

• Architectural design of a standalone Java/Swing-based optimization tool.
• Implementation of linear programming to solve student-to-project assignment problems.
• Creation of an intuitive GUI for data import, settings management, and visualization of results.
• Integration of external libraries such as lp_solve for optimization and iText for reporting.

Excerpt from the Book

Summary of Chapters

1 Project description of JAssign: Outlines the problem of manual student-to-project allocation and sets the project goal to develop a Java-based desktop application as a solution.

2 Creation of a GUI with Java / Swing: Provides a technical overview of the Java Foundation Classes (Swing) used to build the application's graphical user interface and its core components.

3 Implementation: Details the internal class structure, the utilization of external libraries like lp_solve and iText, and the specific packages created for data handling and optimization.

4 Conclusion: Summarizes the project's success in automating the assignment process and confirms the application's platform independence.

5 Appendix: Presents the in-depth mathematical model of the optimization process, including variables, parameters, and constraints.

Keywords

Java, Swing, GUI, linear optimization, student allocation, project assignment, lp_solve, data model, user interface, software architecture, JAssign, constraints, optimization model, desktop application.

Frequently Asked Questions

What is the core purpose of this work?

The work focuses on replacing tedious manual student-to-project assignment processes in university courses with an automated software solution.

What are the central fields of study?

The core fields are software engineering with Java/Swing and operations research, specifically linear optimization.

What is the primary research goal?

To develop a standalone, user-friendly Java application that solves complex assignment problems efficiently.

Which scientific methods are applied?

The application implements linear programming using the Branch-and-bound method to find optimal student assignments.

What is covered in the main section?

The main section describes the architecture, the class structure, the GUI design, and the integration of third-party libraries for optimization and PDF export.

Which keywords best characterize this work?

Java, Swing, GUI, linear optimization, and student allocation are the most essential terms.

How does the application manage data?

It uses a custom Java data model for handling students, projects, and preferences, as a full-scale external database was deemed outside the scope for a standalone tool.

Why was Swing chosen for the GUI?

Swing was chosen because it is the standard toolkit provided with Java, facilitating a platform-independent and robust user interface.

How are assignments optimized?

The application maps the assignment problem into a mathematical model solved by the external lp_solve library.

Can the system handle special constraints?

Yes, the optimization model supports categories, group boundaries, and specific constraints like individual projects or empty projects.