Title :
Research on Multi-project Scheduling Problem Based on Hybrid Genetic Algorithm
Author :
Man, Zhao ; Wei, Tan ; Xiang, Li ; Lishan, Kang
Author_Institution :
Sch. of Comput., China Univ. of Geosci., Wuhan
Abstract :
A simulated annealing genetic algorithm was put forward to solve the resource-constrained multi-project scheduling problem. The ordinary genetic algorithm and simulated annealing algorithm used in this method were improved separately firstly. Then the simulated annealing operations which can overcome the defects of genetic algorithm easy to fall into the local optimal solution were used in the genetic algorithm. The method also inherited the rapid convergence characteristic of genetic algorithm. It was proved by a practical example that this hybrid algorithm improved the deficiencies of genetic algorithm and simulated annealing and can effectively shorten the implementation time of projects. Compared with other heuristic and intelligent methods, this algorithm performs better than them.
Keywords :
genetic algorithms; project management; scheduling; simulated annealing; hybrid genetic algorithm; intelligent methods; resource-constrained multiproject scheduling problem; simulated annealing; Computational modeling; Computer science; Constraint optimization; Genetic algorithms; Geology; Laboratories; Processor scheduling; Resource management; Simulated annealing; Software engineering; Multi-project scheduling; genetic algorithm; heuristic methods; resource constraint; simulated annealing;
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
DOI :
10.1109/CSSE.2008.925