Optimal designs of wireless sensor network by adapted GASA
无线传感器网络的改进GASA优化设计

Wireless sensor network, consisting of lots of sensor nodes, is critical about the cost of entire network. The optimal design of wireless sensor network can minimize the cost of network and fulfill the desired accuracy of detection. An adapted GASA approach, which combines genetic algorithm (GA) and simulated annealing (SA), is developed to optimize the design of wireless sensor network consisted of multi-class, multi-level sensors. The sort-combination operator is specially designed to boost the ability of parallel search of GA and to reduce the complexity of multi-class, multi-level sensors. Optimal feasiblility is also adopted to accelerate the search procession and SA is used to enhance the ability of local search. Finally, the results obtained by GA, SA and the adapted GASA are compared, and three major characters of the adapted GASA are analyzed.