A study of optimal sensor placement based on the improved adaptive simulated annealing genetic algorithms.

This paper presents an improved adaptive simulated annealing genetic algorithms of optimal sensor placement (OSP) based on Modal Assurance Criterion (MAC). Taking the maximum off-diagonal element of the MAC matrix as a target function and the sensor number as a constraint condition, a dualistic coding genetic algorithm is developed which improve the traditional simulation annealing algorithms and use it as an independent operator of GA. Therefore, adaptive crossover and mutation probabilities are adopted to prevent premature convergence. Example results clearly indicate that the method is feasible in optimal sensor placement and number selection, and optimal placement for different accuracy requirement is obtained. [ABSTRACT FROM AUTHOR]