Managing secondary risks with optimal risk response strategy and risk-related resource scheduling

Secondary risks may arise as a result of implementing a risk response plan and may substantially impact the achievement of project objectives. Despite their importance, there is a scarcity of research on scheduling resources to effectively manage these risks. This study presents a pioneering mixed-integer optimization model and a tailored meta-heuristic solution algorithm, specifically designed to determine optimal primary and secondary risk response strategies. To validate our model, we introduce a synthetic data generation framework capable of generating appropriate scenarios based on specific metrics. We apply the model and algorithm to a full factorial numerical experiment constructed using the synthetic data generation algorithm. This allows us to derive managerial insights on secondary risks and the impact that secondary risk responses may have on project objectives. The outcomes of this study provide valuable insights for project managers to better manage both primary and secondary risks.