College - Author 1
College of Engineering
Department - Author 1
Computer Science Department
Advisor
Daniel Frishber, College of Engineering, Computer Science and Software Engineering Department
Funding Source
Cal Poly’s Computer Science and Software Engineering Department
Acknowledgements
The authors acknowledge substantial contributions by Luke Fanguna to the experimental design.
Date
10-2025
Abstract/Summary
In this project we investigate approximation algorithms for the maximum weighted independent set (MWIS) problem in random graphs that approximate real-world graphs, such as social networks. The problem involves finding a large collection of nodes in a network (vertices in a graph) such that no two nodes are directly connected to one another. Applications of the MWIS problem are broad and include clique-finding algorithms as well as the use of large independent sets in distributed algorithms. We build on prior work by the mentor with a SURP 2024 and senior project, in which preliminary findings suggested that a standard greedy algorithm for finding large independent sets, when applied to certain random graphs—can be sped up without any loss in the quality of the solution found. In fact, we found that in the average case the faster version of the algorithm finds a better solution, avoiding the speed-quality tradeoff that is common in algorithm design. We seek to verify and explain this behavior through theory and experiments. This is an opportunity for the mentee to engage in theoretical research and reinforce their algorithmic fundamentals—and to gain experience in experimental design. The mentee will also gain practical, hands-on experience running experiments with standard graph packages for Python, as well as porting the code to C++, parallelizing it, and running it on a computing cluster.
October 1, 2025.
Included in
URL: https://digitalcommons.calpoly.edu/ceng_surp/109