01337950

Component

To strategically locate traffic counting stations across transportation road networks is theoretically a bi-objective integer optimization problem. The problem is formulated with the two objectives considered as: 1) a maximum number of origin-destination (O-D) pairs being separated, and 2) a minimum number of traffic counting stations. This research proposed an ant colony optimization (ACO) based algorithm to solve the traffic counting location problem by explicitly generating the Pareto solutions. Numerical results from two case studies, a small 9-node grid network and a middle size modified Sioux Falls network, were provided to demonstrate the feasibility of the proposed model, although the initial procedure converges too slowly toward high quality solutions. By introducing additional suitable intensification mechanisms, the non-dominated solutions can be attained with significant less number of iterations and ants, which consequently indicates the effectiveness of system, and further verifies the modeling capability of ACO. The performance of the non-dominated solutions can be further investigated and validated using the flow capturing analysis method.

01329018

11-1822

English

22p

2011

Transportation Research Board 90th Annual Meeting

DVD

Figures (6) ; References (15) ; Tables (4)

Algorithms; Location; Mathematical models; Optimization; Origin and destination; Traffic counts; Traffic estimation

Ant colony optimization; Location problems

Data and Information Technology; Highways; I71: Traffic Theory

Transportation Research Board Annual Meeting 2011 Paper #11-1822

TRIS, TRB

Feb 17 2011 5:56PM