A Flexible Scheduling Framework for Repetitive Construction Projects Based on Constraint Programming

Abstract

Scheduling repetitive construction projects (RCPs) is a challenging task due to the nature of the activities involved. It requires careful consideration of both flexibility and computational performance. This paper develops a versatile RCP scheduling framework applicable to multiple construction scenarios, providing greater flexibility than existing models. The framework incorporates various scheduling features for repetitive activities, such as soft logic, multiskilled crews, multimode execution, crew transfers, and continuous or noncontinuous execution. It also offers optional optimization objectives, such as minimizing the overall project duration, total cost, crew interruption time, and number of employed crews. Planners can combine the features of repetitive activities and choose one or more objectives to meet their needs and preferences. The proposed framework is based on constraint programming, which balances computational efficiency and solution quality while remaining user-friendly. The practicality and effectiveness of the framework are verified through three case studies involving five real-life projects. The results demonstrate that the proposed framework can produce RCP schedules with shorter duration, lower costs, or reduced resource utilization compared with those generated by existing models. Efficient scheduling is of great importance for the successful implementation of RCPs. However, it is also a highly challenging task, given that different types of RCPs correspond to different construction scenarios. This paper presents a novel RCP scheduling framework that facilitates the simulation of diverse construction scenarios by incorporating flexibility in the modeling of activities, crews, and objective functions. The framework incorporates multicrew operations for individual activities and facilitates alterations in the construction sequence of units. Moreover, the framework integrates multiskilled crews, offers a variety of execution modes, and supports both intermittent work and strict continuity, as required by the project. Additionally, it provides several objectives, including project duration, project cost, work continuity, total number of crews, or multiples of them. The framework is formulated using the constraint programming technique, which offers the advantages of easy construction, convenient use, and highly efficient solving. Finally, three case studies based on five real-life RCPs are conducted to verify the practicability and validity of the proposed framework. The results demonstrate that the framework outperforms existing models in terms of time, cost, and resource optimization.