Tenant allocation in shopping malls based on deferred acceptance algorithm

In order to enhance customer gathering ability and revenue, matching-based solutions regarding the tenant allocation problem in shopping malls are required. This study addresses the problem using the deferred acceptance algorithm with monetary transfer, aiming to optimize tenant-location matching based on mutual preferences. By implementing and testing the algorithm through simulation experiments, we derive matching results under parameters that are set to be close to reality, which demonstrate strong correlations that have been confirmed in previous literature. This study fills the gap between qualitative rules that should be followed for tenant allocation and its application in real-life situations.