Efficient Layout of Multisensors Using Fuzzy Adaptive Genetic Algorithm

Sensor networks have been widely applied to many fields, such as products management, museum guiding, and indoor positioning. PDAs can now be employed as a feasible companion for museum visitors. The positioning of sensors in a museum that allows suitable contents to be actively recommended to viewers in range is a practical issue that deserves investigation. In this paper, a fuzzy adaptive genetic algorithm is proposed for the layout of multisensors in a given environment. The effectiveness of the selection, mutation and crossover operators employed by conventional genetic algorithm is improved by incorporating a fuzzy mechanism. Furthermore, a new pairwise-elitist selection strategy is introduced.