The Project Research for Optimal Scheduling Based on Intelligent Algorithm

The project management optimization for an important aspect of the scheduling scheme is reasonable to reduce costs, improve quality and shorten the cycle. Traditional project scheduling and optimization methods have been unable to fully meet the rapid development of modern project management needs. The PSO (Particle Swarm Optimization) is a simulation of birds the heuristic search algorithm mechanisms, which function optimization, constrained optimization, minimax problems, such as multi-objective optimization problem. It has become an important branch of the many related optimization fields. Although the project is to optimize the scheduling, many traditional methods can achieve good results, but the particle swarm algorithm can achieve a greater degree of optimization. In this paper, research on the particle swarm optimization of the basic principles of their algorithm for the initial exploration process, compared the effectiveness simulation of particle swarm optimization and traditional genetic algorithm in optimal scheduling of the project. Therefore, the original project plan with the optimal scheduling on the basis of introduction of particle swarm optimization algorithm can get better quality, shorter cycle and fewer costs, and ultimately get the entire optimal project cycle, project quality and project cost.