• DocumentCode
    2096788
  • Title

    A Genetic Algorithm for Solving RCPSP

  • Author

    Zhang, Hua ; Xu, Hao ; Peng, WuLiang

  • Author_Institution
    Sch. of Mech. Eng., Shenyang Ligong Univ. Shenyang, Shenyang, China
  • Volume
    2
  • fYear
    2008
  • fDate
    20-22 Dec. 2008
  • Firstpage
    246
  • Lastpage
    249
  • Abstract
    A genetic algorithm (GA) was proposed to solve the resource constrained project scheduling problem (RCPSP), in which resources are renewable and there is a single mode to perform each activity. This work employed genetic algorithms to schedule project activities to minimize make-span subject to precedence constraints and resources availability. In the genetic algorithm, a new permutation of priority-based encoding scheme was designed in the algorithm, and it inherits all the merits of both the permutation-based encoding scheme and the priority-based encoding scheme. The serial generation scheme was used in decoding scheme to generate project plan. A full factorial computational experiment was set up using the well-known standard instances in PSPLIB, and the algorithm given in this paper was compared with the existing intelligent optimization algorithms, the results reveal that the algorithm is effective for the RCPSP.
  • Keywords
    decoding; encoding; genetic algorithms; minimisation; project management; resource allocation; scheduling; decoding; factorial computational experiment; genetic algorithm; make-span minimization; permutation-based encoding scheme; precedence constraint; priority-based encoding scheme; project plan generation; renewable resource constrained project scheduling problem; resource availability; serial generation scheme; Algorithm design and analysis; Availability; Computer science; Decoding; Encoding; Genetic algorithms; Heuristic algorithms; Mechanical engineering; NP-hard problem; Processor scheduling; genetic algorithm; project scheduling; resource constrained project scheduling problem;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Computational Technology, 2008. ISCSCT '08. International Symposium on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3746-7
  • Type

    conf

  • DOI
    10.1109/ISCSCT.2008.255
  • Filename
    4731613