A Particle Swarm Optimization Algorithm with Crossover for Resource Constrained Project Scheduling Problem

Author

Li, Ming ; Zhang, Yuanbiao ; Jiang, Weigang ; Xie, Jianwen

Author_Institution

Zhuhai Coll., Math. Modeling Innovative Practice Base, Jinan Univ., Zhuhai, China

fYear

2009

fDate

11-12 July 2009

Firstpage

69

Lastpage

72

Abstract

Resource and project optimization scheduling has become the key of the success of researching project in the enterprises. In order to solve the mass resource constrained project scheduling problem, in this paper, an improved particle swarm algorithm (PSO) called particle swarm algorithm with crossover (CPSO) was presented. This improved algorithm is based on PSO and genetic algorithm (GA). Through comparing with SPSO and GA on RCPSP, it is indicated that CPSO not only avoids premature convergence to a high degree, but also keeps a faster convergence rate than SPSO and GA.

Keywords

convergence; genetic algorithms; particle swarm optimisation; project management; scheduling; convergence rate; genetic algorithm; particle swarm optimization algorithm; resource constrained project scheduling problem; Conference management; Convergence; Genetic algorithms; Heuristic algorithms; Innovation management; Iterative algorithms; NP-hard problem; Particle swarm optimization; Project management; Scheduling algorithm; genetic algorithm; particle swarm algorithm with crossover; resource constrained project scheduling problem;

fLanguage

English

Publisher

ieee

Conference_Titel

Services Science, Management and Engineering, 2009. SSME '09. IITA International Conference on

Conference_Location

Zhangjiajie

Print_ISBN

978-0-7695-3729-0

Type

conf

DOI

10.1109/SSME.2009.131

Filename

5233346