DocumentCode
2341522
Title
Hybrid genetic algorithm based on synthetical level of resource conflict for complex construction project scheduling problem
Author
Liu, Tao ; Liu, Min ; Zhang, Ya-Bin ; Zhang, Long
Author_Institution
Dept. of Autom., Tsinghua Univ., Beijing, China
Volume
9
fYear
2005
fDate
18-21 Aug. 2005
Firstpage
5699
Abstract
A hybrid genetic algorithm based on synthetical level of resource conflict for solving complex construction project scheduling problems is proposed, which combines rules-based heuristic with genetic algorithm based on synthetical level of resource conflict, which is used to guide the code, crossover and mutation of genetic algorithm. Also, Researches are made in these aspects such as decomposition method of complex construction project scheduling problem, genetic coding, generating of initial population, crossover and mutation of genetic algorithm. Numerical computation results of different scale problems show that the algorithm has excellent performance for construction project scheduling problem and is suitable for larger-scale construction project scheduling problem with serious resource conflict.
Keywords
construction; genetic algorithms; heuristic programming; knowledge based systems; project management; scheduling; construction project scheduling; crossover; genetic coding; hybrid genetic algorithm; mutation; problem decomposition; resource conflict; rules based heuristic; Automation; Computational modeling; Genetic algorithms; Genetic mutations; Heuristic algorithms; Processor scheduling; Project management; Scheduling algorithm; Simulated annealing; Systems engineering and theory; Project scheduling; complex construction project; genetic algorithm; heuristic; problem decomposition; resource conflict; synthetical level of resource conflict;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location
Guangzhou, China
Print_ISBN
0-7803-9091-1
Type
conf
DOI
10.1109/ICMLC.2005.1527953
Filename
1527953
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