Genetic algorithm approach for locating automatic vehicle identification readers

Abstract

The paper develops an algorithm for optimally locating surveillance technologies with an emphasis on automatic vehicle identification tag readers by maximizing a travel time reliability objective function. The problem is formulated as a quadratic 0-1 optimization problem where the objective function parameters represent benefit factors that capture travel time variability along specified trips. A genetic algorithm is developed to solve the problem and the computational results are presented using data pertaining to a freeway section in San Antonio, Texas, as well as a number of synthetic test cases, to demonstrate the efficacy of the proposed approach.