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https://ruomo.lib.uom.gr/handle/7000/252
Title: | An Animated Demonstration of the Uncapacitated Network Simplex Algorithm |
Authors: | Baloukas, Thanasis Paparrizos, Konstantinos Sifaleras, Angelo |
Type: | Article |
Subjects: | FRASCATI::Natural sciences::Mathematics::Applied Mathematics FRASCATI::Natural sciences::Computer and information sciences |
Keywords: | OR education Combinatorial optimization Educational software |
Issue Date: | 2009 |
Publisher: | INFORMS |
Source: | INFORMS Transactions on Education |
Volume: | 10 |
Issue: | 1 |
First Page: | 34 |
Last Page: | 40 |
Abstract: | Operations Research (OR) instructors use visualizations to help teach graph algorithms and data structures. Algorithm visualization is an illustration of abstract concepts included in computer algorithms, making use of either static or dynamic (animated) computer graphics. In this paper we present new software that includes an animated demonstration of the uncapacitated primal network simplex algorithm. The aim of the animation software is twofold. First, it aims to help OR students understand the algorithm. The algorithm is difficult to grasp for many students because it generates a sequence of rooted trees. Second, it aims to enable OR instructors to explain each iteration of the algorithm visually with minimal effort. The software can be used in combinatorial optimization, graph theory, and similar courses. The software has been implemented as a Java applet, is freely available and highly interactive, and can be accessed through the Web. The software shows the solution process through textual information and depicts the relevant steps in pseudo code using multiple views. |
URI: | https://doi.org/10.1287/ited.1090.0026 https://ruomo.lib.uom.gr/handle/7000/252 |
ISSN: | 1532-0545 1532-0545 |
Other Identifiers: | 10.1287/ited.1090.0026 |
Appears in Collections: | Department of Applied Informatics |
Files in This Item:
File | Description | Size | Format | |
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An_Animated_Demonstration_of_the_Uncapacitated_Network_Simplex_Algorithm.pdf | 1,45 MB | Adobe PDF | View/Open |
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