TY - GEN
T1 - Heuristic algorithms to solve 0-1 mixed integer LP formulations for traffic signal control problems
AU - He, Qing
AU - Lin, Wei Hua
AU - Liu, Hongchao
AU - Head, K. Larry
PY - 2010
Y1 - 2010
N2 - In this paper, three heuristic solution algorithms, (the Dive-and-Fix method, the Ratio-cluster method, and the Cumulative-departure method) are specially designed to solve the traffic signal control problem formulated as a 0-1 mixedinteger linear programming problem with cell transmission model. These three solution algorithms are based on two fundamental approaches. First, the 0-1 mixed-integer linear program is solved via linear relaxation (LR). Second, the noninteger solutions obtained from the LR are converted into the integer solutions by taking advantage of the underlying physical mechanism embedded in the LR solutions that lead to the optimal signal control. In particular, proportional capacities for different approaches and the cumulative exit flow at each intersection obtained from the LR solutions are utilized to determine green time allocation for each approach. It is demonstrated that the near-optimal solutions obtained with these algorithms are very close to the optimal solutions under both uncongested and congested traffic conditions.
AB - In this paper, three heuristic solution algorithms, (the Dive-and-Fix method, the Ratio-cluster method, and the Cumulative-departure method) are specially designed to solve the traffic signal control problem formulated as a 0-1 mixedinteger linear programming problem with cell transmission model. These three solution algorithms are based on two fundamental approaches. First, the 0-1 mixed-integer linear program is solved via linear relaxation (LR). Second, the noninteger solutions obtained from the LR are converted into the integer solutions by taking advantage of the underlying physical mechanism embedded in the LR solutions that lead to the optimal signal control. In particular, proportional capacities for different approaches and the cumulative exit flow at each intersection obtained from the LR solutions are utilized to determine green time allocation for each approach. It is demonstrated that the near-optimal solutions obtained with these algorithms are very close to the optimal solutions under both uncongested and congested traffic conditions.
KW - Cell transmission model
KW - Heuristic algorithms
KW - Linear relaxations
KW - Traffic signal control
UR - http://www.scopus.com/inward/record.url?scp=77957850820&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77957850820&partnerID=8YFLogxK
U2 - 10.1109/SOLI.2010.5551595
DO - 10.1109/SOLI.2010.5551595
M3 - Conference contribution
SN - 9781424471188
T3 - Proceedings of 2010 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2010
SP - 118
EP - 124
BT - Proceedings of 2010 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2010
T2 - 2010 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2010
Y2 - 15 July 2010 through 17 July 2010
ER -