Particle swarm optimization-supported simulation for construction operations

Hong Zhang, C. M. Tam, Heng Li, Jonathan Jingsheng Shi

Research output: Journal article publicationJournal articleAcademic researchpeer-review

26 Citations (Scopus)


This study proposes an integration of particle swarm optimization (PSO) and a construction simulation so as to determine efficiently the optimal resource combination for a construction operation. The particle-flying mechanism is utilized to guide the search process for the PSO-supported simulation optimization. A statistics method, i.e., multiple-comparison procedure, is adopted to compare the random output performances resulting from the stochastic simulation model so as to rank the alternatives (i.e., particle-represented resource combinations) during the search process. The indifference zone and confidence interval facilitate consideration of the secondary performance measure (e.g., productivity) when the main performance measures (e.g., cost) of the competing alternatives are close. The experimental analyses demonstrate the effectiveness and efficiency of the proposed simulation optimization. The study aims to providing an alternative combination of optimization methodology and general construction simulation by utilizing PSO and a statistics method so as to improve the efficiency of simulation in planning construction operations.
Original languageEnglish
Article number009612QCO
Pages (from-to)1267-1274
Number of pages8
JournalJournal of Construction Engineering and Management
Issue number12
Publication statusPublished - 28 Nov 2006


  • Construction management
  • Optimization
  • Particles
  • Simulation

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Industrial relations
  • Strategy and Management


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