DocumentCode
2666986
Title
Study on ant colony optimization for people assign to job problem
Author
Wang, Suxin ; Wang, Leizhen ; Li, Yongqing ; Sun, Jianyong
Author_Institution
Northeastern Univ. at Qinhuangdao, Qinhuangdao, China
fYear
2012
fDate
23-25 May 2012
Firstpage
872
Lastpage
874
Abstract
To deal with people assign to job optimization problem in getting into local minima, people assign to job problem (PATJP) model and ant colony optimization (ACO) are developed for people assign to job optimization problem. In PATJP model, one people can assign to more than one job, and one job can be done by more than one people. People assign to job optimization is searched by ACO, optimization processes tend to get the global solution. Illustration results show that PATJP model and ACO algorithm are effective and offer a way to PATJP.
Keywords
ant colony optimisation; ACO algorithm; PATJP model; ant colony optimization; global solution; job optimization problem; local minima; people assign to job problem model; Algorithm design and analysis; Ant colony optimization; Cybernetics; Educational institutions; Electronic mail; Learning automata; Optimization; Ant Colony Optimization (ACO); Assignment Problem (AP); People Assign to Job Problem (PATJP);
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location
Taiyuan
Print_ISBN
978-1-4577-2073-4
Type
conf
DOI
10.1109/CCDC.2012.6244135
Filename
6244135
Link To Document