Location-Restricted Stable Matching
By: Garret Castro
Potential Business Impact:
Helps teams pick members fairly when they must share space.
Motivated by group-project distribution, we introduce and study stable matching under the constraint of applicants needing to share a location to be matched with the same institute, which we call the Location-Restricted Stable Matching problem (LRSM). We show that finding a feasible matching is NP-hard, making finding a feasible and stable matching automatically NP-hard. We then analyze the subproblem where all the projects have the same capacity, and the applicant population of each location is a multiple of the universal project capacity, which mimics more realistic constraints and makes finding a feasible matching in P. Even under these conditions, a stable matching (a matching without blocking pairs) may not exist, so we look for a matching that minimizes the number of blocking pairs. We find that the blocking pair minimization problem for this subproblem is inapproximable within $|A|^{1-\epsilon}$ for $|A|$ agents and provide an $|A|$-approximation algorithm to show this result is almost tight. We extend this result to show that the problem of minimizing the number of agents in blocking pairs is also inapproximable within $|A|^{1-\epsilon}$, and since there are only $|A|$ agents, this result is also almost tight.
Similar Papers
A Linear Programming Approach to the Super-Stable Roommates Problem
CS and Game Theory
Finds fair roommate pairings, even with tricky choices.
Stable Task Allocation in Multi-Agent Systems with Lexicographic Preferences
Multiagent Systems
Assigns tasks fairly to people who want them.
Structural aspects of the Student Project Allocation problem
CS and Game Theory
Matches students to projects fairly.