A bi-objective traffic counting location problem for origin-destination trip table estimation

In this study, we consider the bi-objective traffic counting location problem for the purpose of origin-destination (O-D) trip table estimation. The problem is to determine the number and locations of counting stations that would best cover the network. The maximal coverage and minimal resource utilization criteria, which are generally conflicting, are simultaneously considered in a multi-objective manner to reveal the tradeoff between the quality and cost of coverage. A distance-based genetic algorithm (GA) is used to solve the proposed bi-objective traffic counting location problem by explicitly generating the non-dominated solutions. Numerical results are provided to demonstrate the feasibility of the proposed model. The primary results indicate that the distance-based GA can produce the set of non-dominated solutions from which the decision makers can examine the tradeoff between the quality and cost of coverage and make a proper selection without the need to repeatedly solve the maximal covering problem with different levels of resource.