  Residential location choice modeling is one of the substantial components of
land use and transportation models. While numerous aggregated mathematical and
statistical approaches have been developed to model the residence choice
behavior of households, disaggregated approaches such as the agent-based
modeling have shown interesting capabilities. In this article, a novel
agent-based approach is developed to simulate the residential location choice
of tenants in Tehran, the capital of Iran. Tenants are considered as agents who
select their desired residential alternatives according to their
characteristics and preferences for various criteria such as the rent,
accessibility to different services and facilities, environmental pollution,
and distance from their workplace and former residence. The choice set of
agents is limited to their desired residential alternatives by applying a
constrained NSGA-II algorithm. Then, agents compete with each other to select
their final residence among their alternatives. Results of the proposed
approach are validated by comparing simulated and actual residences of a sample
of tenants. Results show that the proposed approach is able to accurately
simulate the residence of 59.3% of tenants at the traffic analysis zone level.
