TY - JOUR
T1 - Elastic demand dynamic network user equilibrium
T2 - Formulation, existence and computation
AU - Han, Ke
AU - Friesz, Terry L.
AU - Szeto, W. Y.
AU - Liu, Hongcheng
N1 - Publisher Copyright:
© 2015 Elsevier Ltd.
PY - 2015/11/1
Y1 - 2015/11/1
N2 - This paper is concerned with dynamic user equilibrium with elastic travel demand (E-DUE) when the trip demand matrix is determined endogenously. We present an infinite-dimensional variational inequality (VI) formulation that is equivalent to the conditions defining a continuous-time E-DUE problem. An existence result for this VI is established by applying a fixed-point existence theorem (Browder, 1968) in an extended Hilbert space. We present three computational algorithms based on the aforementioned VI and its re-expression as a differential variational inequality (DVI): a projection method, a self-adaptive projection method, and a proximal point method. Rigorous convergence results are provided for these methods, which rely on increasingly relaxed notions of generalized monotonicity, namely mixed strongly-weakly monotonicity for the projection method; pseudomonotonicity for the self-adaptive projection method, and quasimonotonicity for the proximal point method. These three algorithms are tested and their solution quality, convergence, and computational efficiency are compared. Our convergence results, which transcend the transportation applications studied here, apply to a broad family of VIs and DVIs, and are the weakest reported to date.
AB - This paper is concerned with dynamic user equilibrium with elastic travel demand (E-DUE) when the trip demand matrix is determined endogenously. We present an infinite-dimensional variational inequality (VI) formulation that is equivalent to the conditions defining a continuous-time E-DUE problem. An existence result for this VI is established by applying a fixed-point existence theorem (Browder, 1968) in an extended Hilbert space. We present three computational algorithms based on the aforementioned VI and its re-expression as a differential variational inequality (DVI): a projection method, a self-adaptive projection method, and a proximal point method. Rigorous convergence results are provided for these methods, which rely on increasingly relaxed notions of generalized monotonicity, namely mixed strongly-weakly monotonicity for the projection method; pseudomonotonicity for the self-adaptive projection method, and quasimonotonicity for the proximal point method. These three algorithms are tested and their solution quality, convergence, and computational efficiency are compared. Our convergence results, which transcend the transportation applications studied here, apply to a broad family of VIs and DVIs, and are the weakest reported to date.
UR - https://www.scopus.com/pages/publications/84942582745
UR - https://www.scopus.com/inward/citedby.url?scp=84942582745&partnerID=8YFLogxK
U2 - 10.1016/j.trb.2015.07.008
DO - 10.1016/j.trb.2015.07.008
M3 - Article
AN - SCOPUS:84942582745
SN - 0191-2615
VL - 81
SP - 183
EP - 209
JO - Transportation Research Part B: Methodological
JF - Transportation Research Part B: Methodological
ER -