Different Network Performance Measures in a Multi-Objective Traffic Assignment Problem
(ندگان)پدیدآور
Rassafi, Amir AbbasJamour, DavoodMirzahossein, Hamidنوع مدرک
Textزبان مدرک
Englishچکیده
Traffic assignment algorithms are used to determine possible use of paths between origin-destination pairs and predict traffic flow in network links. One of the main deficiencies of ordinary traffic assignment methods is that in most of them one measure (mostly travel time) is usually included in objective function and other effective performance measures in traffic assignment are not considered. The current study is an endeavor to introduce a solution for this problem by applying a multi-objective optimization idea to traffic assignment models. To do this, first, a problem with three objective functions including travel time, total distance traveled, and the rates of cabin monoxide emissions is studied, and then problem with two objectives combining two well-known assignment approaches i.e. user equilibrium and system optimal is introduced. Using the weighting method to solve the multi-objective problem, and comparing the results, show that the analytical relationships resulted from weighting method is applicable to different networks. Furthermore, comparison of both multi-objective problems and single-objective one (travel time only) showed that the results of proposed model is more appropriate in terms of having a plenary view to this issue, and thus more useful.
کلید واژگان
Multi-Objective Optimizationtraffic assignment
Pareto optimal solution
user equilibrium
system optimization
شماره نشریه
1تاریخ نشر
2013-01-011391-10-12
ناشر
Tarrahan Parseh Transportation Research Instituteسازمان پدید آورنده
Assistant Professor, Department of Civil Engineering, Imam Khomeini International University, Qazvin, Iran.M.Sc. Grad., Department of Civil Engineering, Imam Khomeini International University, Qazvin, Iran.
Ph.D. Candidate, Department of Civil Engineering, Iran University of Science and Technology, Tehran, Iran.
شاپا
2322-259X2538-3728




