Title :
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
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;
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
DOI :
10.1109/IPTC.2010.13
