DocumentCode :
3288248
Title :
Optimization of task allocation and knowledge workers scheduling based-on particle swarm optimization
Author :
Wang Qing ; Zheng Han-chao
Author_Institution :
Manage. Innovation & Evaluation Res. Center, Tianjin Univ. of Commerce, Tianjin, China
fYear :
2011
fDate :
15-17 April 2011
Firstpage :
574
Lastpage :
578
Abstract :
Task allocation and knowledge workers scheduling is known as an NP-hard problem. Scientific task allocation and knowledge workers scheduling is an important part of rational human resources management in enterprises. Particle swarm optimization (PSO) has few parameters to adjust and is easy to implement.This paper uses PSO to research task allocation and knowledge workers scheduling. Particle swarm optimization can obtain better results in a faster and cheaper way compared with other stochastic methods. And the results show that particle swarm optimization is a scientific and efficient method to solve task allocation and knowledge workers scheduling.
Keywords :
human resource management; knowledge management; particle swarm optimisation; personnel; scheduling; stochastic processes; NP-hard problem; human resources management; knowledge workers scheduling; particle swarm optimization; stochastic methods; task allocation optimization; Approximation algorithms; Genetic algorithms; Job shop scheduling; Optimization; Particle swarm optimization; Resource management; Knowledge worker; Particle swarm optimization; Scheduling; Task allocation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electric Information and Control Engineering (ICEICE), 2011 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-8036-4
Type :
conf
DOI :
10.1109/ICEICE.2011.5778029
Filename :
5778029
Link To Document :
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