Papers › Legal Assignments and fast EADAM with consent via classical theory of stable matchings
Legal Assignments and fast EADAM with consent via classical theory of stable matchings
Yuri Faenza, Xuan Zhang
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Gale and Shapley's stable assignment problem has been extensively studied, applied, and extended. In the context of school choice, mechanisms often aim at finding an assignment that is more favorable to students. We investigate two extensions introduced in this framework -- legal assignments and the EADAM algorithm -- through the lens of classical theory of stable matchings. In any instance, the set L of legal assignments is known to contain all stable assignments. We prove that L is exactly the set of stable assignments in another instance. Moreover, we show that essentially all optimization problems over L can be solved within the same time bound needed for solving it over the set of stable assignments. A key tool for this latter result is an algorithm that finds the student-optimal legal assignment. We then generalize our algorithm to obtain the assignment output of EADAM with any given set of consenting students without sacrificing the running time, hence largely improving in both theory and practice over known algorithms. Lastly, we show that the set L can be much larger than the set of stable matchings, connecting legal matchings with certain concepts and open problems in the literature.
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