Network planning multi-objective optimization based on genetic algorithms

In network projects it is generally essential to optimize the best balanced daily amount of resources consumption, which involves economizing each kind of resources and the financial resource, therefore after assigning the proper resources of various tasks in network it is essential to readjust priority to each work to obtain the best utilization ratio of equilibrium optimization. Network Optimization of the project management is of great importance, determining the level of project profits. In this paper, the project time, cost and resouree characteristics of the three objectives are discussed. Based on genetic algorithms a two-stage multi-objective optimization model is proposed. First, we proposed the cost of the time constraints of resources optimization, and optimal balance of resources, and then the network planned multi-objective optimization. After comparing it with the traditional methods for improving the genetic Algorithms in multi-objective optimization, we obtain better optimal results.