TY - JOUR
T1 - Road network pricing and design for ordinary and hazmat vehicles
T2 - Integrated model and specialized local search
AU - López-Ramos, Francisco
AU - Nasini, Stefano
AU - Guarnaschelli, Armando
N1 - Publisher Copyright:
© 2019
PY - 2019/9
Y1 - 2019/9
N2 - In the context of vehicle transportation in congested roads, we propose an optimization framework to integrate the operator decisions on network pricing, regulation, and expansion, while accounting for the shipments of hazardous materials. Current research trends only provide partial modeling integrations of the well-known toll optimization, hazmat transportation, and network design problems. However, the growing complexity of traffic management requires a stronger coordination in the operator decisions. In this paper, a mixed-integer non-linear bi-level problem is introduced to model this integration. The model considers a road network operator (acting as a leader), who maximizes its profit –the toll income minus the costs from roads construction and risk exposure to hazmat transportation–, and vehicles (acting as a follower), who minimize their travel costs –due to traffic congestion and toll charges. We introduce a reformulation approach that approximates this complex integrated problem with arbitrary precision and apply a specialized local search to exploit the structure of such reformulation. This combined resolution strategy relies upon a binary-search-based procedure, which sequentially updates the road prices intervals in such a way that the operator profit is monotonically improved. The effectiveness of the proposed approach is shown on a variety of structural configurations and economic settings, involving 1620 instances tested on the well-known Sioux Falls road network.
AB - In the context of vehicle transportation in congested roads, we propose an optimization framework to integrate the operator decisions on network pricing, regulation, and expansion, while accounting for the shipments of hazardous materials. Current research trends only provide partial modeling integrations of the well-known toll optimization, hazmat transportation, and network design problems. However, the growing complexity of traffic management requires a stronger coordination in the operator decisions. In this paper, a mixed-integer non-linear bi-level problem is introduced to model this integration. The model considers a road network operator (acting as a leader), who maximizes its profit –the toll income minus the costs from roads construction and risk exposure to hazmat transportation–, and vehicles (acting as a follower), who minimize their travel costs –due to traffic congestion and toll charges. We introduce a reformulation approach that approximates this complex integrated problem with arbitrary precision and apply a specialized local search to exploit the structure of such reformulation. This combined resolution strategy relies upon a binary-search-based procedure, which sequentially updates the road prices intervals in such a way that the operator profit is monotonically improved. The effectiveness of the proposed approach is shown on a variety of structural configurations and economic settings, involving 1620 instances tested on the well-known Sioux Falls road network.
KW - Bi-level optimization
KW - Hazmat traffic regulation
KW - Network design
KW - Specialized local search
KW - Toll setting
UR - http://www.scopus.com/inward/record.url?scp=85065483976&partnerID=8YFLogxK
U2 - 10.1016/j.cor.2019.05.006
DO - 10.1016/j.cor.2019.05.006
M3 - Article
AN - SCOPUS:85065483976
SN - 0305-0548
VL - 109
SP - 170
EP - 187
JO - Computers and Operations Research
JF - Computers and Operations Research
ER -