Optimization of Task Allocation and Knowledge Workers Scheduling Based on Ant Colony Algorithm

Author

Wang, Qing ; Liu, Min

Author_Institution

Sch. of Manage., Tianjin Univ. of Commerce, Tianjin, China

fYear

2010

fDate

28-29 Oct. 2010

Firstpage

386

Lastpage

389

Abstract

Scientific task allocation and knowledge workers scheduling is an important part of rational human resources management in enterprises. In this paper, ant colony algorithm is used to research task allocation and knowledge workers scheduling. Ant colony optimization algorithm can reduce the number of optimization iteration and computing time. Elite solution retention tactics is used in iterating process. Then an example is simulated on MATLAB 7.0 platform. The results show that ant colony algorithm is a scientific and efficient method to solve task allocation and knowledge workers scheduling.

Keywords

human resource management; labour resources; optimisation; scheduling; MATLAB 7.0; ant colony algorithm; enterprises; knowledge workers; optimization; rational human resources management; scheduling; task allocation; Approximation algorithms; Classification algorithms; Heuristic algorithms; Job shop scheduling; Processor scheduling; Resource management; Ant colony algorithm; Knowledge worker; Scheduling; Task allocation;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligence Information Processing and Trusted Computing (IPTC), 2010 International Symposium on

Conference_Location

Huanggang

Print_ISBN

978-1-4244-8148-4

Electronic_ISBN

978-0-7695-4196-9

Type

conf

DOI

10.1109/IPTC.2010.13

Filename

5663277