Improved Genetic Algorithm And Its Application In Optimization Design Of Underground Silo

Because it has the advantages of small occupation area, constant temperature and humidity, save storage costs, reduce chemical pollution, the underground warehouse becomes the future development trend of granary. Optimization design method for underground warehouse, to ensure their safety, saving the construction cost is necessary.The process of biological evolution and an intelligent algorithm combined with computer technology and produce. Compared with the traditional optimization method, genetic algorithm can better. Processing discrete, nonlinear problems. Research on genetic algorithm of underground warehouse optimization design application method, can better improve the rationality of the design, so as to reduce the engineering cost, avoid the waste of resources.This paper analyzed and summarized in the genetic algorithm, aiming at the premature convergence of genetic algorithm, appeared in the late evolutionary slow convergence, poor local searching ability shortcomings were improved, adaptive genetic algorithm and applies the improved optimization design for underground silo wall. In this paper, the main work is as follows:Sorting genetic algorithm basic principle, features and operation process, analysis the drawbacks of genetic algorithm and its causes, indicates the direction for the improvement of genetic algorithm;Aiming at shortcomings of the genetic algorithm, proposed an improved adaptive genetic algorithm, The design of a sigmoid adjusting formula of crossover and mutation probability based on, The improved algorithm does not need the same as the basic genetic algorithm, through a number of repeated experiments to select control parameters suitable, At the same time, To overcome the general adaptive genetic algorithm in the initial stage of evolution of elite individuals were nearly the resulting algorithm is likely to fall into a local optimal solution, The test functions of several complex, verify the effectiveness of the improvement measures;Study the general flow in underground warehouse optimization design based on the application of improved genetic algorithm optimization method, and provide new ideas for optimizing design of underground warehouse, to reach a balance between the structural reliability and economy.