To overcome the "prematurity" of standard particle swarm optimization in scheduling problem for solution to resource constrained project, an improved cultural particle swarm optimization is proposed.The algorithm framework is based on the main group space of particle swarm optimization and the knowledge space of cultural algorithm, and both spaces have their own spaces and conduct independent and parallel evolvement to form a "dual evolvement and dual promotion" mechanism and increase the global searching ability and operation efficiency of the algorithm.Meanwhile, to avoid the restriction of self-evolvement for the knowledge space of cultural algorithm, the evolvement mechanism of genetic algorithm is introduced to improve the evolvement operation of knowledge space.Finally, the effectiveness of improved cultural particle swarm optimization in solving the problem of resource constrained project can be validated through comparison of example of human resource scheduling.
Shu-Lin ChangKun-Chang LeeRuey-Rong HuangYu-Hsien Liao
Wu ChunHongyuan JiangYou Xiao-Jian
Anastasis A. SofokleousMarios C. Angelides
Chun-Hao FangLi-Hsiang ShenKai‐Ten Feng