Study on Bi-Objective Traffic Counting Location Optimization Using Ant Colony Method

In order to solve the traffic counting location (TCL) problem, ant colony optimization (ACO) algorithm was introduced, and also some rudimentary numerical results for the TCL set covering model for a simple network were given out. Considering the two goals (maximal coverage and minimal resource utilization) of TCL problem are generally conflicting, this paper tries to incorporate some methods. Two intensification mechanisms are introduced when applying ACO into a similar location model with the same network location data. Then by comparing the optimal results and optimal percentage get, a clearly understanding about applying ACO algorithm into multi- objective location problems is achieved. Through a Pareto ranking selection strategy-Pareto-ranking, we can get the evolution of non-dominated solutions for the Sioux Falls network with 24 nodes, 76 links, and 182 O-D pairs. Also the performance of these non-dominated solutions can be further investigated using the flow capturing analysis method.