Comparative Analysis of Greedy, Gale-Shapley, and Score-Based Methods for Optimal Project Allocation
Year: 2024
Type: article
Abstract: The project allocation problem is essential in various fields, including academic and organizational settings, where efficient, stable, and satisfying assignments are crucial for maximizing engagement and productivity. This paper presents a comparative analysis of three distinct algorithms for project allocation: the Greedy Algorithm, the Stable Matching Algorithm (Gale-Shapley), and a Score-Based Allocation Method. The Greedy Algorithm prioritizes computational efficiency, while the Gale-Shapley algorithm focuses on stability, and the Score-Based AllocationMethod allows flexibility in balancing multiple criteria. Our findings reveal that while the Stable Matching Algorithm ensures stable matches, the Score-Based Method optimizes for overall satisfaction based on different objectives, offering valuable insights into the trade-offs involved in choosing each approach.
Author: Ru (Johnny) Zhang
Institution: Université Paris 1 Panthéon-Sorbonne
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4404823578