The Resource Levelling Based on Particle Swarm Optimization
Jingwen Zhang · Systems Engineering · 2008
This paper puts forward an assumption that applying the Particle Swarm Optimization(PSO) to the issue of resource levelling and optimizaing of model development project.An algorithm model of Particle Swarm Optimization suitable for the resource levelling is proposed,methods for resource levelling and optimizing based on non-key activities dynamic time variance are designed,evaluation function and evolution equation for resource intensity and actual time of starting of activities are established,and the algorithm procedure is also described.Finally,the resource intensity obtained by PSO is reduced by 88.38% compared to the initial schedule,by 58.42%,74.48% compared to the P3 solftware,Project2002 result according to the case analysis.The feasibility and effectivity of the algorithm model are validated,and several secondary optimium schedules are also obtained.