Station deployment of workspace measuring and positioning system based on improved adaptive genetic algorithm

Workspace measuring and positioning system (wMPS) is a multistation intersection system based on photoelectric scanning. Since wMPS is dependent on the multistation synergy to achieve the coordinate measuring, the station layout optimization is an important problem. Optimal station topological geometry based on improved adaptive genetic algorithm was proposed. Firstly, the positioning accuracy, coverage area and cost were taken as objectives to establish the multiobjective optimization function. Secondly, through combining evolving algebra attenuation factor with adaptive genetic algorithm, improved adaptive genetic algorithm optimization process was established according to multiobjective function. Finally, simulation analysis for layout optimization algorithm of 2~4 stations was performed. The results show that compared with adaptive genetic algorithm, the proposed method can converge to the optimal solution within 10~20 generations and get better objective function value. Therefore, this method is able to improve wMPS measuring performance in spatial layout design.