A new allocation rule for the housing market problem with ties

Xinsheng Xiong, Xianjia Wang and Kun He ()
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Xinsheng Xiong: Wuhan University
Xianjia Wang: Wuhan University
Kun He: Huazhong University of Science and Technology

Journal of Combinatorial Optimization, 2022, vol. 43, issue 1, No 6, 98-115

Abstract: Abstract We address a general housing market problem with a set of agents and a set of houses. Each agent has a weak ordinal preference list that allows ties on houses as well as an initial endowment; moreover, each agent wishes to reallocate to a better house on the housing market. In this work, we reduces the complexity of the family of top trading cycles algorithms by selecting a specific house from the preferred set during the trading phase. The rule of construction digraphs is used to select an appropriate house. Based on these digraphs, we propose an extended top trading cycles algorithm with complexity $$O(n^{2} r)$$ O ( n 2 r ) , where $$n$$ n is the number of agents and $$r$$ r is the maximum length of ties in the preference lists. The algorithm complexity is lower than that of the state-of-the-art algorithms. We show that the proposed algorithm is individually rational, Pareto efficient, and strategy-proof. It thus overcomes the limitations of a classic top trading cycles algorithm, and features Pareto efficiency and strategy-proofness on the weak preference domain.

Keywords: Algorithmic game theory; Resource allocation; Pareto efficiency; Strategy-proofness; Top trading cycles algorithm (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10878-021-00727-z

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