Abstract
Optimization of road space allocation (RSA) from a network perspective is computationally challenging. Analogues to the Network Design Problem (NDP), RSA can be classified as a NP-hard problem. In large scale networks when the number of alternatives increases exponentially, there is a need for an efficient method to reduce the number of alternatives as well as a computational approach to reduce the computer execution time of the analysis. A heuristic algorithm based on Genetic Algorithm (GA) is proposed to efficiently select Transit Priority Alternatives (TPAs). In order to reduce the execution time, the GA is modified to implement two parallel processing techniques: A High Performance Computing (HPC) technique using Multi-threading (MT) and a High Throughput Computing (HTC) technique. The advantages and limitations of the MT and HTC techniques are discussed. Moreover, the proposed framework allows for a TPA to be analyzed by a commercial package which is a significant provision for large scale networks in practice.
Keywords
- Central Processing Unit
- High Performance Computing
- Network Design Problem
- Large Scale Network
- Parallel Genetic Algorithm
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References
Bard, J.F.: Practical bilevel optimization: algorithms and applications. Kluwer Academic Publishers, Boston (1998)
Ben-Ayed, O., Blar, C.E.: Computational difficulties of Bilevel Linear Programming. Operations Research 38, 556–560 (1990)
Fan, W., Machemehl, R.B.: Optimal Transit Route Network Design Problem with Variable Transit Demand: Genetic Algorithm Approach. Journal of Transportation Engineering 132, 40–51 (2006)
Foster, I.T., Zhao, Y., Raicu, I., Lu, S.: Cloud Computing and Grid Computing 360-Degree Compared. In: Grid Computing Environments Workshop, GCE 2008 (2008)
Mesbah, M., Sarvi, M., Ouveysi, I., Currie, G.: Optimization of Transit Priority in the Transportation Network Using a Decomposition Methodology. Transportation Research Part C: Emerging Technologies (2010)
Shimizu, K., Ishizuka, Y., Bard, J.F.: Nondifferentiable and two-level mathematical programming. Kluwer Academic Publishers, Boston (1997)
Strohmaier, E., Dongarra, J.J., Meuer, H.W., Simon, H.D.: Recent trends in the marketplace of high performance computing. Parallel Computing 31, 261–273 (2005)
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© 2012 Springer-Verlag GmbH Berlin Heidelberg
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Mesbah, M., Sarvi, M., Tan, J., Karimirad, F. (2012). High Throughput Computing Application to Transport Modeling. In: Gaol, F., Nguyen, Q. (eds) Proceedings of the 2011 2nd International Congress on Computer Applications and Computational Science. Advances in Intelligent and Soft Computing, vol 145. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28308-6_7
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DOI: https://doi.org/10.1007/978-3-642-28308-6_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28307-9
Online ISBN: 978-3-642-28308-6
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