An enhanced differential evolution（EDE） algorithm is proposed to solve the problem that given a monitor area with time-varying differential requirements to place sensor nodes with different parameters such reliability

lifespan

energy and mobile ability

fulfilling maximum area coverage performance. A self-adaptive mutation strategy and control parameters of algorithm such as F and CR according to the individual situation of the population in the process of the algorithm is adopt in the EDE to enhance its optimization ability. The proposed EDE also adopt the strategy of hybrid differential evolution and simulated annealing algorithm to improve its local search ability. Simulation results shows that the proposed EDE achieves better the coverage performance than the primitive differential evolution（DE） algorithm

which proves the effectiveness of the improned algorithm EDE.