Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.
Our ultimate goal is to design transportation net-
works whose dynamic performance metrics (e.g. pas-
senger throughput, passenger delay, and insensitivity
to weather disturbances) are optimized. Here the fo-
cus is on optimizing static features of the network that
are known to directly affect the network dynamics.
First, we present simulation results which support a
connection between maximizing the first non-trivial
eigenvalue of a network’s Laplacian and superior air-
port network performance. Then, we explore the ef-
fectiveness of a tabu search heuristic for optimizing
this metric by comparing experimental results to the-
oretical upper bounds. We also consider generating
upper bounds on a network’s algebraic connectivity
via the solution of semidefinite programming (SDP)
relaxations. A modification of an existing subgraph
extraction algorithm is implemented to explore the
underlying regional structures in the U.S. airport net-
work, with the hope that the resulting localized struc-
tures can be optimized independently and reconnected
via a “backbone” network to achieve superior network
performance.
