There is the possibility of complete 3D modeling using terrestrial laser scanner. To have a complete coverage of the target region for the scan, the device must be located in various locations and carried out measurement operations. Nevertheless, the movement to increase the deployment requires more field measurements which respectively will increase the cost and time. In this paper, the goal is to provide a tool to assess the selected locations for the deployment of terrestrial laser scanners. In this regard, to achieve this goal, the genetic optimization algorithm is being used. In the proposed method, the total registered point cloud implementation of all stations in the range of scanning devices is used as the search space for the genetic algorithm. The cost function with two goals, one reduction in occlusion areas and the other is to take fewest possible points for placements. By selecting a random set of candidate locations for placement as an initial response, the algorithm will start to obtain optimal layout placement and in the search space, during successive iterations by applying the selection operators, crossover and mutation will be provided. In this process, the optimal choice of device placement is automatic and repetitive and ensure correct alignment will achieve with the minimum number of points required for full measurement. The results show the genetic optimization algorithm to optimize the laser scanner device placements across a large number of the selected candidate. Thereby, it can be created a tool to assess the efficiency of the selected placements. The chance of 99% scanning of the area with absolute certainty using the proposed method with the least possible number of stations was established.