• DocumentCode
    2261559
  • Title

    Multi-Objective Optimization in Construction Project Based on a Hierarchical Subpopulation Particle Swarm Optimization Algorithm

  • Author

    Wang, Weibo ; Feng, Quanyuan

  • Author_Institution
    Sch. of Inf. Sci. & Technol., Southwest Jiaotong Univ., Chengdu
  • Volume
    1
  • fYear
    2008
  • fDate
    20-22 Dec. 2008
  • Firstpage
    746
  • Lastpage
    750
  • Abstract
    Comprehensive trade-off control on construction time, cost and quality is main aspect of construction project management, and it is significant for improving the benefits of construction projects. This paper presents mathematical models for time, cost and quality separately, and a multi-objective optimization model for time-cost-quality trade-off optimization is set up by synthesizing weighted single-objective models. In a case study, comparing to standard particle swarm optimization (SPSO) and differential evolution algorithm (DE), the most satisfied decision results can be obtained by applying the hierarchical subpopulation particle swarm optimization algorithm (HSPSO) proposed in this paper to solve time-cost-quality trade-off problems. Finally, exhaustive enumeration is given to verify the effectiveness of the models and the feasibility of solution method.
  • Keywords
    construction industry; particle swarm optimisation; project management; construction cost; construction project management; construction quality; construction time; differential evolution algorithm; hierarchical subpopulation particle swarm optimization algorithm; mathematical model; multiobjective optimization; Ant colony optimization; Cost function; Genetic algorithms; Information science; Information technology; Integrated circuit modeling; Mathematical model; Particle swarm optimization; Project management; Quality management; Multi-objective Optimization; Particle Swarm Optimization algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3497-8
  • Type

    conf

  • DOI
    10.1109/IITA.2008.99
  • Filename
    4739671