  With the growing attention towards developing the multimodal transport system
to enhance urban mobility, there is an increasing need to construct new,
rebuild or expand existing infrastructure to facilitate existing and
accommodate newly generated travel demand. Therefore, this paper develops a
bilevel model to simultaneously determine the location and capacity of the
transfer infrastructure to be built considering elastic demand in a multimodal
transport network. The upper level problem is formulated as a mixed integer
linear programming problem, while the lower level problem is the capacitated
combined trip distribution assignment model that depicts both destination and
route choices of travelers via the multinomial logit formula. To solve the
model, the paper develops a matheuristics algorithm that integrates a Genetic
Algorithm and a successive linear programming solution approach. Numerical
studies are conducted to demonstrate the existence and examine two Braess like
paradox phenomena in a multimodal transport network. The first one states that
under fixed demand constructing parking spaces to stimulate the usage of Park
and Ride service could deteriorate the system performance, measured by the
total passengers travel time, while the second one reveals that under variable
demand increasing the parking capacity for the Park and Ride services to
promote the usages may fail, represented by the decline in its modal share.
Meanwhile, the last experiment suggests that constructing transfer
infrastructures at distributed stations outperforms building a large transfer
center in terms of attracting travelers using sustainable transit modes.
