Parallel computing framework for optimizing construction planning in large-scale projects

Amr Kandil, Khaled El-Rayes

Research output: Contribution to journalArticlepeer-review


Available construction optimization models can be used to generate optimal tradeoffs between construction time and cost, however their application in optimizing large-scale projects is limited due to their extensive and impractical computational time requirements. This paper presents the development of a parallel computing framework in order to circumvent this limitation. The framework incorporates a multi-objective genetic algorithm module that identifies optimal trade-offs between construction time and cost; and a parallel computing module that distributes genetic algorithm computations over a network of processors. The performance of the framework is evaluated using 150 experiments that represent various combinations of project sizes and numbers of processors. The results of this analysis illustrate the robust capabilities of the developed parallel computing framework in terms of its efficiency in reducing the computational time requirements for large-scale construction optimization problems, and its effectiveness in obtaining high quality solutions identical to those generated by a single processor.

Original languageEnglish (US)
Pages (from-to)304-312
Number of pages9
JournalJournal of Computing in Civil Engineering
Issue number3
StatePublished - Jul 2005


  • Construction management
  • Cost control
  • Distributed processing
  • Information management
  • Optimization
  • Planning
  • Time factors

ASJC Scopus subject areas

  • Computer Science Applications
  • Civil and Structural Engineering


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