• DocumentCode
    1946851
  • 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
  • Volume
    1
  • fYear
    2008
  • fDate
    12-14 Dec. 2008
  • Firstpage
    390
  • Lastpage
    394
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Software Engineering, 2008 International Conference on
  • Conference_Location
    Wuhan, Hubei
  • Print_ISBN
    978-0-7695-3336-0
  • Type

    conf

  • DOI
    10.1109/CSSE.2008.925
  • Filename
    4721769