Resource Leveling Optimization of Network Schedule Based on Particle Swarm Optimization with Constriction Factor

Aiming at the issue of resource leveling optimization of network schedule, a discrete nonlinear mixed integer optimization model is established and an improved PSO is also proposed. In the process of establishing the leveling optimization model, resource intensity variance which is used to measure the proportionality of resource is selected as the evaluation function index. On PSO improving, for that the standard PSO is easier to converge too early when dealing with complicated problems, constriction factor is introduced into PSO to control flying speed of particles and to enhance local searching ability of this algorithm, and then improved PSO is proposed. Finally, through case study, a satisfied optimized result is obtained, and it also proves that the leveling optimization model and the optimized algorithm which are established in this paper are simple and applicable, and they are also easy to operate and be transplanted.