DocumentCode
1591791
Title
A New Optimization Method for Resource Leveling
Author
Tian, WenJie ; Liu, JiCheng
Author_Institution
Autom. Inst., Beijing Union Univ., Beijing, China
Volume
2
fYear
2010
Firstpage
175
Lastpage
178
Abstract
An improved adaptive immune clone selection algorithm (ICSA) is proposed, which is a new heuristic intelligent optimization algorithm. We apply the method in the resource leveling; the properties are discussed and analyzed. The experimental results show that proposed methods have better performances such as good and fast global convergence, strong robustness, insensitive to initial values, simplicity of implementation.
Keywords
artificial immune systems; convergence; adaptive immune clone selection algorithm; global convergence; heuristic intelligent optimization algorithm; implementation simplicity; initial values insensitivity; optimization method; resource leveling; Automation; Bones; Cloning; Convergence; Data structures; Genetic mutations; Immune system; Optimization methods; Particle swarm optimization; Signal processing algorithms; antibody; global convergence; immune clone selection algorithm; mutation; resource leveling;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Modeling and Simulation, 2010. ICCMS '10. Second International Conference on
Conference_Location
Sanya, Hainan
Print_ISBN
978-1-4244-5642-0
Electronic_ISBN
978-1-4244-5643-7
Type
conf
DOI
10.1109/ICCMS.2010.220
Filename
5421102
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