Genetic algorithm approach for locating automatic vehicle identification readers

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.