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Solving the Student-Project Allocation Problem with Preferences over Projects Using a Multi-start Local Search

  • 2026
  • OriginalPaper
  • Chapter
Published in:
Authors
Le Quoc Anh
Nguyen Nhu Son
Son Thanh Cao
Hoang Huu Viet
Published in
Multi-disciplinary Trends in Artificial Intelligence
Publisher
Springer Nature Singapore

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Abstract

This chapter delves into the Student-Project Allocation Problem with Preferences over Projects (SPA-P), a complex matching problem that involves assigning students to projects based on their preferences while adhering to capacity constraints. The paper introduces a multi-start local search algorithm designed to find maximum stable matchings in large-scale instances of SPA-P. The algorithm employs a perturbation mechanism to escape local optima and iteratively refines random matchings by eliminating undominated blocking pairs. Experimental results show that the proposed algorithm outperforms existing methods, such as SPA-P-approx and SPA-P-approx-promotion, in terms of stable matching size and computational efficiency. The study also explores the algorithm's performance across various scenarios, highlighting its robustness and scalability. The findings suggest that the multi-start local search algorithm is a promising approach for addressing the challenges of automated student-project matching systems.
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next chapter A Small Language Model and Domain-Specific Resources for Vietnamese Public Services
Title
Solving the Student-Project Allocation Problem with Preferences over Projects Using a Multi-start Local Search
Authors
Le Quoc Anh
Nguyen Nhu Son
Son Thanh Cao
Hoang Huu Viet
Copyright Year
2026
Publisher
Springer Nature Singapore
Book
Multi-disciplinary Trends in Artificial Intelligence

Print ISBN: 978-981-9549-59-7

Electronic ISBN: 978-981-9549-60-3

Copyright Year: 2026

DOI
https://doi.org/10.1007/978-981-95-4960-3_1
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