Bi-objective optimization of the scheduling of risk-related resources for risk response

Risk response is a crucial component of project risk management, playing a key role in mitigating the adverse effects of risks. However, the implementation of such risk response relies on the utilization of appropriate risk-related resources. Given the scarcity of these resources, their proper scheduling and allocation are critical. To address this issue, this paper introduces a flow-based continuous-time bi-objective optimization model for risk-related resource planning. The proposed model is then applied to a case study, deriving the global optimal solution based on the tuned parameters. Moreover, we develop a tailored rule-based metaheuristic algorithm for the model. The algorithm incorporates improved random key-based population initialization and a rule-based genetic operator, facilitating the application of the proposed model to large-scale projects. The computational results of the case study and numerical experiments not only validate the effectiveness of the algorithm, but also emphasize the importance of the precautionary principle and redundant resources in project risk management.