Optimum design of sensor arrays via simulation-based multivariate calibration

This paper is concerned with the optimum design of sensor arrays (i.e., electronic noses or tongues) using simulation experiments. The proposed design method considers multiple criteria simultaneously for the evaluation of sensor arrays, and a multiple objective tabu search algorithm was adapted to search for a number of Pareto optimum array designs in terms of those criteria. The evaluation of a candidate sensor array is based on its multivariate calibration model, which is efficiently estimated from well-designed simulation experiments. The method can be used to optimize the design of both linear and nonlinear sensor arrays.