• DocumentCode
    3546050
  • Title

    Particle swarm optimization method for resource-constrained project scheduling problem

  • Author

    Zhang, Kai ; Zhao, Guorong ; Jiang, Jing

  • Author_Institution
    Dept. of Control Eng., Naval Univ. of Aeronaut. & Astronaut., Yantai, China
  • fYear
    2009
  • fDate
    16-19 Aug. 2009
  • Abstract
    Particle swarm optimization (PSO) algorithm for resource-constrained project scheduling problem (RCPSP) is introduced in the paper. The activities sequence encoded with the simple code rule by the code order is just corresponding to the project scheme fulfilling the precedence constraint, and it is convenient to calculate the start time scope (solution space) of all activities in the project. The precedence constrain of activities are processed directly by the repair strategy and the resource constrain of the project are processed indirectly by calculating the fitness value of the particle in the process of PSO evolutions, thus avoid the complex project arrangement and take advantage of the swarm characteristic of PSO to find the best particle fulfilling the optimization object in the solution space. The application to typical project shows us the validity of using PSO to solve RCPSP.
  • Keywords
    optimisation; scheduling; particle swarm optimization; resource-constrained project scheduling problem; start time scope; Constraint optimization; Control engineering; Equations; Extraterrestrial measurements; Instruments; Mathematical model; Particle measurements; Particle swarm optimization; Particle tracking; Scheduling algorithm; Particle; optimization; repair strategy; resource-constrained project scheduling problem; swarm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic Measurement & Instruments, 2009. ICEMI '09. 9th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-3863-1
  • Electronic_ISBN
    978-1-4244-3864-8
  • Type

    conf

  • DOI
    10.1109/ICEMI.2009.5274706
  • Filename
    5274706