TY - GEN
T1 - Mixed-integer Programming for a New Bus-lane Reservation Problem
AU - Wu, Peng
AU - Chu, Feng
AU - Ada, Che
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/10/30
Y1 - 2015/10/30
N2 - In this paper, we investigate a new bus-lane reservation problem in transportation network, which aims to optimally decide which lanes to be reserved for the exclusive use of buses and design bus transit paths for bus lines to achieve time-efficient bus transit with stop time window constraints. However, an exclusive bus-lane may cause negative impact on non-bus vehicles running on its adjacent non-reserved lanes as it reduces their available lanes. The objective of the problem is to minimize the total negative impact caused by reserved lanes. To address this problem, we first formulate a mixed-integer non-linear program and its complexity is proved to be NP-hard. Then, the nonlinear model is equivalently transformed into an linear one. Furthermore, properties of the problem are analyzed to reduce the search space for optimal solutions and tighten the proposed linear model. Finally, it is solved using commercial optimization software CPLEX. Computational results on randomly generated instances show the effectiveness of the proposed approach.
AB - In this paper, we investigate a new bus-lane reservation problem in transportation network, which aims to optimally decide which lanes to be reserved for the exclusive use of buses and design bus transit paths for bus lines to achieve time-efficient bus transit with stop time window constraints. However, an exclusive bus-lane may cause negative impact on non-bus vehicles running on its adjacent non-reserved lanes as it reduces their available lanes. The objective of the problem is to minimize the total negative impact caused by reserved lanes. To address this problem, we first formulate a mixed-integer non-linear program and its complexity is proved to be NP-hard. Then, the nonlinear model is equivalently transformed into an linear one. Furthermore, properties of the problem are analyzed to reduce the search space for optimal solutions and tighten the proposed linear model. Finally, it is solved using commercial optimization software CPLEX. Computational results on randomly generated instances show the effectiveness of the proposed approach.
UR - http://www.scopus.com/inward/record.url?scp=84950301555&partnerID=8YFLogxK
U2 - 10.1109/ITSC.2015.447
DO - 10.1109/ITSC.2015.447
M3 - 会议稿件
AN - SCOPUS:84950301555
T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
SP - 2782
EP - 2787
BT - Proceedings - 2015 IEEE 18th International Conference on Intelligent Transportation Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th IEEE International Conference on Intelligent Transportation Systems, ITSC 2015
Y2 - 15 September 2015 through 18 September 2015
ER -