In structural health monitoring (SHM), sensor network scale and sensor distribution decisions are critical since sensor network performance and system cost are greatly affected. A quantitative sensor placement optimization method with covariance matrix adaptation evolutionary strategy (CMAES) is presented in this paper. A damage detection probability model is developed for ultrasonic guided wave sensor networks. Two sample problems are presented in this paper. One is for structure with irregular damage distribution probability, and the other is for an E2 aircraft wing section. The reliability of this genetic and evolutionary optimization method is proved in this study. Sensor network configurations with minimum missed-detection probability are obtained from the results of evolutionary optimization. The tradeoff relationship between optimized sensor network performance and the number of sensors is also presented in this paper.