Research On Vertical Optimization Of Line Using Genetic Algorithms

Ii is difficult to express all the influencing factors with a complete model in this state because there are many influencing factors involved in the establishment of the vertical optimization model in vertical optimization of Line.At the same time,it is limited by the applicable conditions of the existing optimization algorithm,which leads to the difference between the optimized solution and the actual situation.Therefore,it is still an important subject for vertical optimization to establish a vertical optimization model with a variety of influencing factors and the model solution obtained by the optimization algorithm is close to the actual situation.For the purpose of the research of line vertical optimization algorithm based on genetic algorithm,the theory,method and algorithm involved in this paper are studied deeply.The main research contents are as follows.(1)Based on the goal of the most provincial total cost of the main project,a vertical optimization model is established,and the construction cost is determined by considering the depth and length of the bridge and tunnel,and the total cost of the subgrade is calculated according to the total length of the excavation,and the construction cost of the station is determined according to the project cost of the station.In addition to considering the basic minimum slope length,maximum slope limit,maximum slope difference and control point elevation,the constraint condition also restricts the station floor limit slope of the station.(2)In order to make the initial vertical feasible to solve the ground trend well,according to the central smoothness method for the ground line smooth treatment.The number of feasible solutions of the initial vertical is determined by the ground fluctuation method and the screening method.Linear quasi-legality and various constraint processing methods are used to determine the position of the variable slope point of the feasible solution of the initial vertical.(3)On the basis of the feasible solution of the initial vertical of the generated line,the mileage and elevation of the variable slope point of the initial vertical population are determined by normal distribution method and uniform distribution method.At the same time,the method of solving the fitness function,the selection operator,the crossover operator and the mutation operator in the genetic process are designed and adjusted reasonably,so that the optimization model can be solved better.(4)Using C # to write genetic algorithm program,the whole model to solve the algorithm to verify.Then take a certain section of subway as an example to test and analyze,verify the rationality of its optimization algorithm and the feasibility and practicability of the program.