Distributed Computing for the Optimization of Large-Scale Construction Projects
Available construction time-cost trade-off analysis models can be used to generate trade-offs between these two important objectives, however, their application is limited in large-scale construction projects due to their impractical computational requirements. This paper presents the development of a scalable and multi-objective genetic algorithm that provides the capability of simultaneously optimizing construction time and cost large-scale construction projects. The genetic algorithm was implemented in a distributed computing environment that utilizes a recent standard for parallel and distributed programming called the message passing interface (MPI). The performance of the model is evaluated using a set of measures of performance and the results demonstrate the capability of the present model in significantly reducing the computational time required to optimize large-scale construction projects.
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