Multiobjective Model for Locating Automatic Vehicle Identification Readers

Abstract

The problem of locating automatic vehicle identification (AVI) readers on a transportation network is one worth considering. AVI readers are strategically located to catch a maximum number of trips and cover a maximum number of origin-destination (O-D) pairs using a minimum number of AVI readers. There are three possible objectives when deciding locations for AVI readers: (a) a minimum number of AVI readers, (b) maximum O-D coverage, and (c) a maximum number of trips (or AVI readings). To satisfy all three objectives as much as possible, the problem is formulated as a multiobjective integer-optimization problem. A distance-based genetic algorithm is applied to solve this multiobjective AVI reader-location problem by explicitly generating the nondominated solutions. Numerical results are presented to demonstrate the feasibility of the proposed multiobjective model. The procedure proposed holds great promise for the development of a well-configured AVI system that can achieve a balance between quality and cost of coverage (i.e., trade-off between cost and coverage requirements).