Optimizing the number of crews working in parallel and their work sequence to minimize project duration and cost for repetitive construction projects

Abstract

Abstract Scheduling repetitive construction projects poses a significant challenge in optimally utilizing multiple concurrent crews and sequencing their work to minimize project duration and cost. To address this challenge, this study presents the development of a multi-objective scheduling optimization model for repetitive construction projects consisting of three modules. First, a scheduling module ensures the harmonious coordination of multiple concurrent crews for each activity while considering varying productivity rates, work continuity constraints, and project precedence relationships. Second, a cost module incorporates various contractual cost components to enable a thorough evaluation of project costs and provides flexibility to contractors encountering different contract terms. Third, an optimization module utilizes a genetic algorithm to identify optimal combinations of crews working in parallel and their optimal work sequence, to simultaneously minimize project duration and cost. An application example from the literature was analyzed to validate the model and demonstrate its superiority over previous models. The results showed significant reductions of 8% and 0.78% in project duration and overall costs, respectively, compared to previous models. Furthermore, the capabilities of the model were demonstrated through a real-life case study involving a highway development and renovation project, highlighting its practical benefits and effectiveness in a real-world construction scenario.