Hybrid multi-mode simulation and optimization for subarea scheduling in heavy industrial construction

Scheduling heavy industrial projects is challenging due to their size and complexity. Three-dimensional space and its discipline-specific tasks are an important asset in congested industrial sites, yet are not easily scheduled early in planning when detailed information is lacking. Although recent approaches have focused on enhancing space and crew management, effective scheduling of large-scale industrial projects with several interdependent constraints remains difficult. A comprehensive, hybrid planning framework capable of developing an efficient, high-level schedule accounting for uncertainties in bidding and execution is proposed. The framework employs simulation and optimization tools to determine best durations/modes in multi-mode activity networks and uses dynamic data adoption to continuously plan during project progression. The proposed framework uses historical information and expert opinion to automatically create a near-optimized schedule while considering various uncertainties. The proposed approach is tested and demonstrated with an illustrative example and an actual case study of industrial construction in Alberta, Canada.