Optimal sensor placement has become an important topic in the field of structural health monitoring and damage identification for obtaining the most testing results possible with limited resources. To effectively place strain sensors, a new optimal strain sensor placement (OSSP) method, which uses a hybrid algorithm of an improved discrete particle swarm optimization (DPSO) algorithm and a clonal selection algorithm (CSA) to optimize the novel fitness function, is proposed and applied to a Laxiwa arch dam. The results show that the clonal selection and discrete particle swarm hybrid algorithm (CSA-DPSO) has stronge global optimization ability, and the proposed strain fitness function has advantages in capability for both strain modal assurance and modal strain energy criteria. The scheme determined by the proposed strain sensor placement method can accurately identify strain mode shapes. This method can provide some guidance for OSSP in a variety of structures in the future.