Scheduling of Lane Closures Using Genetic Algorithms with Traffic Assignments and Distributed Simulations
Publication: Journal of Transportation Engineering
Volume 130, Issue 3
Abstract
In past research, several versions of hybrid genetic algorithm–simulation methodology have been proposed for scheduling of multiple lane closures that aims to minimize a network’s total traffic delay. The genetic algorithm is used as a search engine for generation of lane closure schedule, while a microscopic traffic simulation model is employed to calculate the total network travel time under each lane closure scenario. A difficulty in implementing this methodology practically is the long computing time required, due to the many simulation runs needed to evaluate the average total network travel time of each feasible schedule. This paper applies the precondition technique, standard error criterion, and termination criterion to reduce the number of necessary simulation runs. As a further improvement, traffic simulations are distributed in different processors of a multiprocessor machine. To further reduce the computing time, a two-stage hybrid genetic algorithm methodology has been proposed in this paper. This two-stage methodology consists of a hybrid genetic algorithm–traffic assignment methodology as the first stage, followed by a hybrid genetic algorithm–distributed simulation methodology as the second stage. The traffic assignment model is used to replace the traffic simulation model in the estimation of total network travel time in stage 1. The applications of the improvement techniques have been demonstrated through a hypothetical problem involving 20 lane closure requests in a network consisting of 986 links, 397 nodes, and 22 origin-destination zones. Together, these improvement techniques contributed to up to 87% reduction in waiting time for a solution of the example problem.
Get full access to this article
View all available purchase options and get full access to this article.
References
Chan, W. T., Fwa, T. F., and Tan, C. Y.(1994). “Road maintenance planning using genetic algorithms. I: Formulation.” J. Transp. Eng., 120(5), 693–709.
Chang, Y. Y., Sawaya, O. B., and Ziliaskopoulos, A. K. (2001). “A tabu search based approach for work zone scheduling.” Proc., 80th Annual Meeting, Transportation Research Board, Washington, D.C.
Cheu, R. L., and Ma, W. (2002). “An improved genetic algorithm-simulation methodology for lane closure scheduling.” Proc., 81st Annual Meeting, Transportation Research Board, Washington, D.C.
Federal Highway Administration. (1995). The TSIS user’s guide, Office of Traffic Safety and Operations, Washington, D.C.
Fwa, T. F., Chan, W. T., and Tan, C. Y.(1994). “Generic algorithm programming of road maintenance and rehabilitation.” J. Transp. Eng., 122(3), 246–253.
Fwa, T. F., Cheu, R. L., and Muntasir, A. (1998). “Scheduling of pavement maintenance to minimize traffic delays.” Transportation Research Record 1650, Transportation Research Board, Washington, D.C., 28–35.
Goldberg, D. E. (1989). Genetic algorithm in search optimization and machine learning, Addison-Wesley, Reading, Mass.
Michalewicz, Z. (1996). Genetic programs, 3rd Ed., Springer, Berlin.
Montgomery, C. D., and Runger, C. G. (1999). Applied statistics and probability for engineers, 2nd Ed., Wiley, New York.
Muntasir, A. (1998). “Scheduling of pavement maintenance activities.” MS thesis, Dept. of Civil Engineering, National Univ. of Singapore, Singapore.
Quadstone Ltd. (2000). PARAMICS Modeller V3.0 user guide and reference manual, Edinburgh, U.K.
Ross, S. M. (1990). A course in simulation, Macmillan, New York.
Thomas, R. (1991). Traffic assignment techniques, Gower, Brookfield, Mass.
Van Aerde, M. (1999). INTEGRATION release 2.20 for Windows user’s guide, Van Aerde and Associates, Blacksburg, Va.
Wang, Y., Cheu, R. L., and Fwa, T. F. (2002). “Highway maintenance scheduling using genetic algorithm with microscopic traffic simula-tion” Proc., 81st Annual Meeting, Transportation Research Board, Washington D.C.
Information & Authors
Information
Published In
Copyright
Copyright © 2004 American Society of Civil Engineers.
History
Received: Oct 22, 2002
Accepted: May 14, 2003
Published online: Apr 15, 2004
Published in print: May 2004
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.