Project Based On Genetic Algorithm Period-cost Optimization Model For Analysis

In recent years,With the rapid development of computer information engineering technology,and improve the level of project management,making it possible to multi-objective quantitative construction engineering project management,and the main content of the project objective quantitative management is a combination of the construction period and cost optimization, a relatively reasonable to determine the construction period can bring benefits to the project to some extent. However, Opposing each other between the construction period and cost of construction engineering project and unified feature increases the project multi-objective quantitative management work more difficult.For a long time,people use the traditional way to study the construction period and cost optimization, however, the traditional way to deal with the problem of optimal exist limitations, in order to solve the problem, the artificial intelligence algorithm, genetic algorithm (ga) arises at the historic moment. In view of the genetic algorithm in solving the optimization problem of many advantages, such as high solving efficiency and its good search feature, more suitable for the processing schedule cost optimization problem. Therefore, this article attempts to use this method to solve the established model of quantitative analysis of construction cost, and by sharing technology to control the convergence of solution and uniformity, made solution are toward the optimal trade off surface convergence, so as to find the satisfactory solution of the problem.Verify the feasibility and effectiveness of the model has been established, to improve the comprehensive benefit of the project has the very big significance.According to current research on construction project cost in the construction period optimization results, considering project resource equilibrium configuration, and the time value of money, and then build a system of time limit for a project cost quantification, more scientific and reasonable multi-target comprehensive optimization,Then use a combination of genetic algorithm with adaptive value allocation principle of Shared technology during the process of comprehensive interpretation model,Finally through a real case to verify the model, and USES the computer program for solving, to analyze and validate the model and feasibility of application of summary model of deficiency, and puts forward to improvement.