Difference between revisions of "A heuristic decomposition method for large-scale traffic assignment: Aburra Valley case study"
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Traffic assignment is one of the most important stages in transportation planning; however, its application to real case studies in medium- to largesized cities makes the solution of the model difficult because of the scale and high computational complexity related to the combinatorial and non-linear nature of the problem. The aim of this paper is to present a decomposition method based on sub-region analysis, and a simple heuristic rule for solving large-scale traffic assignment problems. This reduces the total amount of variables and equations of the model and offers a practical solution in a reasonable computing time. The proposed traffic assignment model is applied to the multimodal main road network of the Aburra Valley, Colombia. Such an application of a great amount of variables and equations converts the model into a large-scale problem. The proposed method considerably reduces the computational complexity of the problem, and it reveals accurate solutions in an execution time which is reasonable for such a large-scale model. | Traffic assignment is one of the most important stages in transportation planning; however, its application to real case studies in medium- to largesized cities makes the solution of the model difficult because of the scale and high computational complexity related to the combinatorial and non-linear nature of the problem. The aim of this paper is to present a decomposition method based on sub-region analysis, and a simple heuristic rule for solving large-scale traffic assignment problems. This reduces the total amount of variables and equations of the model and offers a practical solution in a reasonable computing time. The proposed traffic assignment model is applied to the multimodal main road network of the Aburra Valley, Colombia. Such an application of a great amount of variables and equations converts the model into a large-scale problem. The proposed method considerably reduces the computational complexity of the problem, and it reveals accurate solutions in an execution time which is reasonable for such a large-scale model. | ||
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Link to material: http://aprendeenlinea.udea.edu.co/revistas/index.php/ingenieria/article/view/17225/14890 | Link to material: http://aprendeenlinea.udea.edu.co/revistas/index.php/ingenieria/article/view/17225/14890 | ||
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[[Category:Transportation]] | [[Category:Transportation]] | ||
Revision as of 03:47, 11 April 2014
by: Laura Lotero, Patricia Jaramillo & Claudia Rave
Abstract
Traffic assignment is one of the most important stages in transportation planning; however, its application to real case studies in medium- to largesized cities makes the solution of the model difficult because of the scale and high computational complexity related to the combinatorial and non-linear nature of the problem. The aim of this paper is to present a decomposition method based on sub-region analysis, and a simple heuristic rule for solving large-scale traffic assignment problems. This reduces the total amount of variables and equations of the model and offers a practical solution in a reasonable computing time. The proposed traffic assignment model is applied to the multimodal main road network of the Aburra Valley, Colombia. Such an application of a great amount of variables and equations converts the model into a large-scale problem. The proposed method considerably reduces the computational complexity of the problem, and it reveals accurate solutions in an execution time which is reasonable for such a large-scale model.
Link to material: http://aprendeenlinea.udea.edu.co/revistas/index.php/ingenieria/article/view/17225/14890
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