Reactive Scheduling for Repetitive Projects Based on Integrated Crew Interruption and Soft Logic Strategies

Repetitive projects are frequently disrupted by uncertain events, resulting in delays and cost overruns. Responding to the challenge, this study investigates the problem of reactive scheduling in repetitive projects. First, the study introduces an interruption approach from the perspective of crews and designs a comprehensive reactive strategy that integrates crew work interruption and soft logic strategies. Subsequently, the problem is delineated. In order to minimize the deviations between the new and old scheduling plans, the concept of repetitive project reactivity cost is defined, and a mixed integer programming model is formulated for the minimization of total cost. Furthermore, a genetic algorithm (GA) is designed to solve the proposed model. Finally, a comparative experiment is conducted using a highway project as an illustrative example to demonstrate the effectiveness of the proposed strategy. Extensive large-scale simulations are employed to validate its applicability. The results indicate that crew interruption significantly reduces interruption costs compared with activity interruption. Moreover, the strategy proposed in this study is more effective in reducing total costs and shortening duration compared to the two individual strategies of crew interruptions and soft logic. This research can provide decision support for repetitive project managers to deal with uncertain disturbances.