DocumentCode :
1395849
Title :
Optimal Lane Reservation in Transportation Network
Author :
Fang, YunFei ; Chu, Feng ; Mammar, Saïd ; Zhou, MengChu
Author_Institution :
Lab. IBISC, Univ. of Evry-Val d´´Essonne, Evry, France
Volume :
13
Issue :
2
fYear :
2012
fDate :
6/1/2012 12:00:00 AM
Firstpage :
482
Lastpage :
491
Abstract :
This work studies a lane reservation problem in a transportation network. It aims to design task paths and optimally select lanes to be reserved in a transportation network. In this problem, each lane has limited residual capacity, which is the lane capacity that can be used for the tasks causing no delay in this lane. If the residual capacity of a lane is not large enough to allow tasks to use it, the reservation of this lane is necessary. Once reserved, the lane can be used by the tasks only. Therefore, the travel time in this reserved lane is less than that when it is not reserved. Such lane reservation strategy ensures that each task can transport the commodity from its source to destination within a given travel time. However, this reserved lane generates traffic impact on nonreserved lanes. The objective of the problem is to minimize the total impact of all reserved lanes on nonreserved lanes subject to the timely completion of all the concerned tasks. In this paper, two integer linear programming models are, for the first time, formulated. The complexity of the problem is demonstrated to be non-deterministic polynomial-time hard. Then, an optimal algorithm based on the cut-and-solve method is developed for the problem. The computational results of randomly generated network instances up to 120 nodes and 468 arcs show that the proposed algorithm significantly outperforms the direct use of an optimization solver of CPLEX.
Keywords :
integer programming; linear programming; minimisation; road traffic; transportation; CPLEX; cut-and-solve method; integer linear programming; lane capacity; nondeterministic polynomial-time hard; optimal algorithm; optimal lane reservation; optimization solver; residual capacity; task path; traffic impact; transportation network; travel time; Complexity theory; Computational modeling; Delay; Educational institutions; Upper bound; Vehicles; Cut-and-solve method; linear programming; optimization; traffic control; transportation systems;
fLanguage :
English
Journal_Title :
Intelligent Transportation Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1524-9050
Type :
jour
DOI :
10.1109/TITS.2011.2171337
Filename :
6099683
Link To Document :
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